From cc6746a95669cfd69a49e32a3e6c2e5a42ce2546 Mon Sep 17 00:00:00 2001 From: DVIDIA Date: Mon, 9 Nov 2026 08:07:58 -0500 Subject: [PATCH 1/2] Cache verified learning arrays and check reachable action references --- .github/workflows/ci.yml | 2 + README.md | 8 + .../camera-action-export-cache-v01/README.md | 27 ++ .../benchmark.py | 104 +++++ .../cli-proof-prior-source.json | 13 + .../cli-proof.json | 153 +++++++ .../results-prior-source.json | 117 +++++ .../results.json | 117 +++++ .../camera-action-v02-preflight/README.md | 17 + .../evidence-20261109/cases.json | 1 + .../evidence-20261109/measurements.json | 1 + .../evidence-20261109/protocol.json | 1 + .../evidence-20261109/report.json | 1 + .../camera-action-v02-preflight/preflight.py | 401 ++++++++++++++++++ .../test_preflight.py | 177 ++++++++ .../tests-20261109.log | 25 ++ .../tests-source-parser-development.log | 64 +++ docs/camera-action-export-cache-v01.md | 89 ++++ docs/camera-action-v02-preflight.md | 147 +++++++ docs/camera-action-v02-proposal.md | 35 ++ pyproject.toml | 2 +- src/dvidia_training/camera_action_cache.py | 382 +++++++++++++++++ src/dvidia_training/footage_pipeline.py | 4 + tests/test_camera_action_cache.py | 272 ++++++++++++ tests/test_camera_cache_cli.py | 45 ++ 25 files changed, 2204 insertions(+), 1 deletion(-) create mode 100644 benchmarks/camera-action-export-cache-v01/README.md create mode 100644 benchmarks/camera-action-export-cache-v01/benchmark.py create mode 100644 benchmarks/camera-action-export-cache-v01/cli-proof-prior-source.json create mode 100644 benchmarks/camera-action-export-cache-v01/cli-proof.json create mode 100644 benchmarks/camera-action-export-cache-v01/results-prior-source.json create mode 100644 benchmarks/camera-action-export-cache-v01/results.json create mode 100644 benchmarks/camera-action-v02-preflight/README.md create mode 100644 benchmarks/camera-action-v02-preflight/evidence-20261109/cases.json create mode 100644 benchmarks/camera-action-v02-preflight/evidence-20261109/measurements.json create mode 100644 benchmarks/camera-action-v02-preflight/evidence-20261109/protocol.json create mode 100644 benchmarks/camera-action-v02-preflight/evidence-20261109/report.json create mode 100644 benchmarks/camera-action-v02-preflight/preflight.py create mode 100644 benchmarks/camera-action-v02-preflight/test_preflight.py create mode 100644 benchmarks/camera-action-v02-preflight/tests-20261109.log create mode 100644 benchmarks/camera-action-v02-preflight/tests-source-parser-development.log create mode 100644 docs/camera-action-export-cache-v01.md create mode 100644 docs/camera-action-v02-preflight.md create mode 100644 src/dvidia_training/camera_action_cache.py create mode 100644 tests/test_camera_action_cache.py create mode 100644 tests/test_camera_cache_cli.py diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index cd80389..8b6bb1c 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -78,6 +78,8 @@ jobs: dvidia-piper-recovery --help dvidia-piper-reliability --help dvidia-training-doctor --json + - name: Verify pinned learning caches + run: python -m unittest tests.test_camera_action_cache tests.test_camera_cache_cli tests.test_camera_action_export tests.test_camera_action_model -v - name: Test footage, visual training and loopback studio run: python -m unittest tests.test_footage_data tests.test_footage_train tests.test_footage_pipeline tests.test_footage_benchmark tests.test_training_studio tests.test_doctor tests.test_coverage tests.test_episode_tape tests.test_reaction tests.test_reaction_metrics tests.test_reaction_convergence tests.test_reaction_benchmark tests.test_motor_memory tests.test_motor_metrics tests.test_motor_benchmark tests.test_observations tests.test_observation_models tests.test_motion tests.test_motion_benchmark tests.test_transition_model tests.test_transition_pilot tests.test_transition_cli tests.test_embodiment_calibration tests.test_embodiment_cli tests.test_reference_sim -v diff --git a/README.md b/README.md index 0bc20bc..f027851 100644 --- a/README.md +++ b/README.md @@ -6,6 +6,14 @@ [Recorded demo](https://huggingface.co/spaces/Dvidia/dvidia-training) · [Synthetic datasets](https://huggingface.co/datasets/Dvidia/dvidia-training-examples) · [Pilot models](https://huggingface.co/Dvidia/dvidia-training-pilot) +**[Verified local learning cache](docs/camera-action-export-cache-v01.md).** +The **0.1.3.dev5 preview** adds `dvidia-train cache` to reuse verified camera/action +features with caller-pinned data, split and source identities. On one 1,000-sample +training episode, validated loads took a median **2.952 ms**, versus **1.636 s** +for strict raw export; numeric values and model dataset identity were unchanged. +Cache hits verify derived bytes, not raw recordings. This speeds repeated local +data preparation; it does not improve the frozen **5/64** placement result. + **[Camera-to-action skill v0.1](docs/camera-action-v01.md).** The **0.1.3.dev4 preview** adds a local demonstration-to-action learning loop: 25 Hz RGB-D, 50 Hz measured joints and demonstrated targets, a compact CPU diff --git a/benchmarks/camera-action-export-cache-v01/README.md b/benchmarks/camera-action-export-cache-v01/README.md new file mode 100644 index 0000000..0dfb3d8 --- /dev/null +++ b/benchmarks/camera-action-export-cache-v01/README.md @@ -0,0 +1,27 @@ +# Camera-action export cache: bounded local benchmark + +`results.json` is the byte-identical result from one first-protocol-ordered training episode (`train-00-goal0-teacher`). No fitting, native simulation or confirmation-episode data was used. + +| Operation | Wall time | +|---|---:| +| Unchanged strict export | 1.636 s | +| Strict export + cache preparation | 1.053 s | +| Three validated cache loads | 2.952 / 2.831 / 3.214 ms | + +All 1,000 feature/target samples, groups, provenance and model dataset identity match exactly for every load. This episode's strict-export features are float32, as stored in the cache. Multi-episode strict export promotes float32 values to float64; caching those values as float32 preserves numeric values and model identity but does not preserve the combiner's array dtype or NPY bytes. + +The median ratio was 554× for repeated preparation of this one warm shared-host episode. The 1,137,058-byte cache replaces repeated validation of an episode containing 6,011 files and 197,398,789 bytes for this use; original recordings remain intact. A cache hit does **not** reverify those raw files. No inference-speed, grip-success, task-success or hardware claim follows from these timings. + +Host scope: arm64 macOS, Python 3.12.9, NumPy 2.5.3. CPU and memory sysctl metadata was unavailable in the sandbox. Peak process RSS was 163,463,168 bytes including strict export and preparation. Validation is timed; Python imports and explicit post-load equality comparison are excluded. There was no OS file-cache flush or exclusive CPU reservation. The shorter cache-build time is an order/cache effect, not a faster strict exporter. + +Three data-preparation measurements are retained. The first reporter attempt completed data operations but failed on restricted optional host metadata; its local cache/pins directory remains intact. The corrected reporter persisted progress and produced the prior-source measurement in `results-prior-source.json` (SHA-256 `5e28976319740bc6da85c833084c87b0df4a48aea62f0c249a1007c9cddbc922`, cache module `ad79c142b51798281c3f2ce0645662e24da8a21e778ae7785ce9c2c44102c185`). + +Review then identified a Windows portability issue: setting the temporary hard link read-only before unlinking its temporary name can prevent cleanup. The writer now unlinks the still-writable temporary name before sealing the complete target read-only. The current measurement reran the same episode in a fresh directory, bound to cache module `9191f2eb9f96bd09d4f711c31966a583bd938853a874e6018f8ddebfb0bc00d8`. Times across these shared-host runs are not a controlled before/after comparison or evidence that this cleanup fix accelerated export. There were no native/model trials or benchmark-scene replacements. Original source bytes and local directories are preserved. + +The focused CLI/cache/export suite passes 25 tests, including cleanup order, no-overwrite behavior, disk-space refusal and fixtures that skip unavailable platform link privileges. The cache tests are included in the existing Ubuntu/macOS/Windows CI matrix; local execution here was macOS only. A fresh offline `0.1.3.dev5` wheel install outside the checkout loaded the new cache using independently retained benchmark pins and matched all 19 frozen source hashes plus the cache source. It also passed wrong-split refusal, original robot stages, and footage help checks without installing native simulation dependencies. + +- Result SHA-256: `a4b4b1675e8d157ee9808e556e37c6c697134f529a084488b930299028084353`. +- Dataset SHA-256: `856205dec60ad1c452373fabfd1a75e72a875ff76075971ac2ed26ada8a8bdf3`. +- Protocol SHA-256: `576851e321034a0f6d3cb4d0818b3a5ca97975fcc6f2c7fa30b07ffd203a2d76`. +- `cli-proof.json` records fresh installed-wheel source, inspection/load, wrong-split refusal and existing CLI checks, outside the three timed loads. `cli-proof-prior-source.json` retains the earlier source-bound checks. +- [Usage, trust boundary and reproduction](../../docs/camera-action-export-cache-v01.md). diff --git a/benchmarks/camera-action-export-cache-v01/benchmark.py b/benchmarks/camera-action-export-cache-v01/benchmark.py new file mode 100644 index 0000000..ab7588d --- /dev/null +++ b/benchmarks/camera-action-export-cache-v01/benchmark.py @@ -0,0 +1,104 @@ +#!/usr/bin/env python3 +"""One registered training episode: strict export, cache build, three verified hits. + +No fitting, teacher execution, simulator or confirmation-scene reads. Output is +fresh and outside the source study. Wall times include validation, not imports. +""" +import argparse +from hashlib import sha256 +import json +from pathlib import Path +import platform +import resource +import subprocess +import time + +import numpy as np + +from dvidia_training import camera_action_cache as cache +from dvidia_training import camera_action_export as export +from dvidia_training import camera_action_model as model + + +def array_hash(value): + return sha256(np.ascontiguousarray(value).tobytes()).hexdigest() + + +def main(): + parser = argparse.ArgumentParser(description=__doc__) + parser.add_argument('study'); parser.add_argument('output'); parser.add_argument('--protocol-sha256', required=True) + args = parser.parse_args() + root = Path(args.study).resolve(); out = Path(args.output).absolute() + if root == out or root in out.parents: + raise ValueError('Proof output must be outside source study.') + out.mkdir() # fresh output, no rerun/overwrite + def progress(event): + with (out/'progress.jsonl').open('a') as stream: + stream.write(json.dumps(event, sort_keys=True) + '\n') + protocol = json.loads((root/'protocol.json').read_text()) + if sha256((root/'protocol.json').read_bytes()).hexdigest() != args.protocol_sha256: + raise ValueError('Unexpected protocol identity.') + entry = next(r for r in protocol['rosters']['demonstrations'] if r['case']['split'] == 'train') + relative = 'episodes/demonstrations/' + entry['id'] + directory = root/relative + metadata_before = {name: sha256((directory/name).read_bytes()).hexdigest() + for name in ('recording.json','integrity.json','rollout.json')} + start = time.perf_counter(); strict = export.export_episode(directory); strict_s = time.perf_counter()-start + progress(dict(stage='strict_export', seconds=strict_s)) + start = time.perf_counter() + pins = cache.build_cache(root, out/'cache', expected_protocol_sha256=args.protocol_sha256, + split='train', stage='demonstrations', attempt_ids=[entry['id']]) + build_s = time.perf_counter()-start + progress(dict(stage='strict_cache_build', seconds=build_s)) + (out/'pins.json').write_text(json.dumps(pins, sort_keys=True, indent=2)+'\n') + (out/'pins.json').chmod(0o444) + loads, checks = [], [] + for _ in range(3): + start = time.perf_counter() + loaded = cache.load_cache(out/'cache', expected_manifest_sha256=pins['manifest_sha256'], + expected_protocol_sha256=args.protocol_sha256, expected_split='train', expected_source_sha256=pins['source_sha256']) + loads.append(time.perf_counter()-start) + progress(dict(stage='verified_hit', index=len(loads), seconds=loads[-1])) + # Equality comparisons are outside the timed hit; byte/hash/semantic + # validation performed by load_cache itself is inside every timed hit. + checks.append(dict(features=np.array_equal(strict['features'], loaded['features']), + targets=np.array_equal(strict['targets'], loaded['targets']), groups=strict['groups']==loaded['groups'], + provenance=strict['provenance']==loaded['provenance'], + dataset_sha256=model._dataset(strict, blind=False)[-1]==model._dataset(loaded, blind=False)[-1])) + if not all(all(c.values()) for c in checks): + raise ValueError('Cache output differs from strict export.') + metadata_after = {name: sha256((directory/name).read_bytes()).hexdigest() for name in metadata_before} + if metadata_before != metadata_after: + raise ValueError('Source episode metadata changed during benchmark.') + hardware = dict(platform=platform.platform(), machine=platform.machine(), python=platform.python_version(), numpy=np.__version__) + if platform.system() == 'Darwin': + for name in ('machdep.cpu.brand_string','hw.physicalcpu','hw.memsize'): + query = subprocess.run(['sysctl','-n',name], check=False, text=True, capture_output=True) + hardware[name] = query.stdout.strip() if query.returncode == 0 else {'status':'unavailable', 'reason':'host metadata query refused'} + files = [p for p in directory.rglob('*') if p.is_file()] + result = dict(schema='dvidia.camera-action-export-cache-benchmark/v1', scope=__doc__.strip(), + attempt_id=entry['id'], split='train', protocol_sha256=args.protocol_sha256, + source_identity=cache.source_identity(), pins=pins, episode_metadata_sha256=metadata_after, + samples=len(strict['groups']), features_sha256=array_hash(strict['features']), targets_sha256=array_hash(strict['targets']), + groups_sha256=model.digest(strict['groups']), provenance_sha256=model.digest(strict['provenance']), + equality_checks=checks, strict_export_seconds=strict_s, strict_cache_build_seconds=build_s, + verified_hit_seconds=loads, verified_hit_median_seconds=float(np.median(loads)), + strict_to_hit_median_ratio=strict_s/float(np.median(loads)), + source_episode_files=len(files), source_episode_bytes=sum(p.stat().st_size for p in files), + cache_bytes=sum(p.stat().st_size for p in (out/'cache').iterdir()), + peak_process_rss=resource.getrusage(resource.RUSAGE_SELF).ru_maxrss, + peak_process_rss_units='bytes' if platform.system()=='Darwin' else 'KiB', + hardware=hardware, raw_source_reverified_on_hit=False, native_runs=0, fitting_runs=0, + qualification_changed=False, + timing_caveats=['One fixed training episode, one strict export and one strict cache build, then three sequential cache hits.', + 'Existing OS file cache was not flushed; shared laptop, no exclusive CPU reservation.', + 'Imports are excluded; validation and source-hash checks are included. Equality comparison is outside timed hit.', + 'RSS is cumulative process high water including strict export and build, not isolated cache memory.', + 'No evidence of faster inference, improved control, whole-dataset throughput or hardware readiness.']) + (out/'benchmark.json').write_text(json.dumps(result, sort_keys=True, indent=2)+'\n') + print(json.dumps({k:result[k] for k in ('attempt_id','samples','strict_export_seconds','strict_cache_build_seconds', + 'verified_hit_seconds','strict_to_hit_median_ratio','cache_bytes')}, indent=2)) + + +if __name__ == '__main__': + main() diff --git a/benchmarks/camera-action-export-cache-v01/cli-proof-prior-source.json b/benchmarks/camera-action-export-cache-v01/cli-proof-prior-source.json new file mode 100644 index 0000000..95de1c7 --- /dev/null +++ b/benchmarks/camera-action-export-cache-v01/cli-proof-prior-source.json @@ -0,0 +1,13 @@ +{ + "scope": "Fresh Python CLI processes, cached artifact only, no training or raw-data verification.", + "valid_inspect_exit": 0, + "valid_inspection": { + "dataset_sha256": "856205dec60ad1c452373fabfd1a75e72a875ff76075971ac2ed26ada8a8bdf3", + "raw_source_reverified_on_hit": false, + "samples": 1000, + "scope": "Cached derived learning arrays, not raw recording revalidation, source authentication, training, native simulation or hardware qualification.", + "status": "verified" + }, + "wrong_split_exit": 1, + "wrong_split_refused": true +} diff --git a/benchmarks/camera-action-export-cache-v01/cli-proof.json b/benchmarks/camera-action-export-cache-v01/cli-proof.json new file mode 100644 index 0000000..c89cf38 --- /dev/null +++ b/benchmarks/camera-action-export-cache-v01/cli-proof.json @@ -0,0 +1,153 @@ +{ + "benchmark_sha256": "a4b4b1675e8d157ee9808e556e37c6c697134f529a084488b930299028084353", + "commands": [ + { + "arguments": [ + "cache", + "source" + ], + "exit_code": 0, + "stderr_sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", + "stdout_sha256": "202c68ad9cdad7e37e01c0bc5d87232faa40119db15fdc224408b4df07d75ca6" + }, + { + "arguments": [ + "cache", + "inspect", + "/cache", + "--manifest-sha256", + "94d018de48b3eb63381a0e1169f9a7b4f6a67b40b3abbc91fe3d490cf3cdd8a0", + "--protocol-sha256", + "576851e321034a0f6d3cb4d0818b3a5ca97975fcc6f2c7fa30b07ffd203a2d76", + "--split", + "train", + "--source-sha256", + "0ab01145c66d651eaca96d763b4bec1706327f2cdd4bd8665d05056cbdd6f677" + ], + "exit_code": 0, + "stderr_sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", + "stdout_sha256": "882d31b2ee0a92e2ffa4851433c76034bb8c588497759f1b35f0735700288407" + }, + { + "arguments": [ + "cache", + "load", + "/cache", + "--manifest-sha256", + "94d018de48b3eb63381a0e1169f9a7b4f6a67b40b3abbc91fe3d490cf3cdd8a0", + "--protocol-sha256", + "576851e321034a0f6d3cb4d0818b3a5ca97975fcc6f2c7fa30b07ffd203a2d76", + "--split", + "train", + "--source-sha256", + "0ab01145c66d651eaca96d763b4bec1706327f2cdd4bd8665d05056cbdd6f677" + ], + 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Equality comparison is outside timed hit.", + "RSS is cumulative process high water including strict export and build, not isolated cache memory.", + "No evidence of faster inference, improved control, whole-dataset throughput or hardware readiness." + ], + "verified_hit_median_seconds": 0.002952292008558288, + "verified_hit_seconds": [ + 0.002952292008558288, + 0.0028308329929132015, + 0.0032142080017365515 + ] +} diff --git a/benchmarks/camera-action-v02-preflight/README.md b/benchmarks/camera-action-v02-preflight/README.md new file mode 100644 index 0000000..1728948 --- /dev/null +++ b/benchmarks/camera-action-v02-preflight/README.md @@ -0,0 +1,17 @@ +# Camera/action v0.2 numerical limiter preflight + +The original constant-target reference limiter and the projected endpoint agree +within the predeclared 1e-12 native-unit tolerance on all 4,242 bounded numerical +cases. Closed-form projection is not universally bitwise identical. No robot +skill, model training or physical motion was tested. + +See [scope, results and reproduction](../../docs/camera-action-v02-preflight.md). +The v0.1 source, recordings, models and results are unchanged. + +`evidence-20261109/` preserves the protocol and complete case manifest written +before the numerical comparisons, all per-case results, 24 negative checks and +the final report. `tests-20261109.log` records 20 passing tests; +`tests-source-parser-development.log` retains an earlier parser failure found +and corrected before the frozen evidence run. The proof binds the exact script, +tests, original source files and original PiPER XML. It contains only synthetic +numerical vectors and receipts. diff --git a/benchmarks/camera-action-v02-preflight/evidence-20261109/cases.json b/benchmarks/camera-action-v02-preflight/evidence-20261109/cases.json new file mode 100644 index 0000000..2d634d1 --- /dev/null +++ b/benchmarks/camera-action-v02-preflight/evidence-20261109/cases.json @@ -0,0 +1 @@ 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diff --git a/benchmarks/camera-action-v02-preflight/evidence-20261109/measurements.json b/benchmarks/camera-action-v02-preflight/evidence-20261109/measurements.json new file mode 100644 index 0000000..7fe12af --- /dev/null +++ b/benchmarks/camera-action-v02-preflight/evidence-20261109/measurements.json @@ -0,0 +1 @@ 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diff --git a/benchmarks/camera-action-v02-preflight/evidence-20261109/protocol.json b/benchmarks/camera-action-v02-preflight/evidence-20261109/protocol.json new file mode 100644 index 0000000..079226e --- /dev/null +++ b/benchmarks/camera-action-v02-preflight/evidence-20261109/protocol.json @@ -0,0 +1 @@ +{"bindings":{"base_source_commit":"ab9082e1ee2b2cc91c7c5fd3f1358727b3789c66","limiter_ast_sha256":"a5356fb9e1bd8b1dc6e6b2b14d657fbe625e018ba8d1e5e668ba4d11191f7921","limiter_source_lines":[307,312],"original_defaults":{"control_dt":0.02,"jaw_target_rate_m_s":0.05,"joint_target_rate_rad_s":1.5,"timestep":0.001},"piper_xml":{"bytes":14537,"git_blob_sha1":"8b8962d805b519bc25f764316abf65bb3f6d8f37","path":"agilex_piper/piper.xml","sha256":"a7b5b5d3b2a68d5c553b2ee9665d54a422bd8bf1fa6f3251bc11834993d37098"},"scope":"Only the two reference updates are executed; XML is parsed without MuJoCo.","source_sha256":{"src/dvidia_training/camera_action_export.py":"2c4e30587605edc0342150a93430a70ed0559c3ee3eda17d93c5670831370b02","src/dvidia_training/camera_action_model.py":"e9a9c4d1d0f16fc7c91cac3ca2e6560d0532370ab78a2af5a4ec84425c23932f","src/dvidia_training/piper_action_capture.py":"da037b2198cf7d2f3a9aa40fc19a4c0f5cc375a22c5dd75606e2c1856f6efc7f","src/dvidia_training/piper_imitation.py":"849f66512c58441a240cd20230fcc58691234ddd254c5bbcbfd76abc21b14868","src/dvidia_training/piper_task.py":"e66a44a8df4e7a8ee42e4f3866f889f8797cdfb8e2688a146e09b75d2c76664f","src/dvidia_training/robot_profiles.lock.json":"4b2ee2ca675aceb2f826983cb3082a3e08e9aa0ff419b23078abcff08ebcc6fe"},"upstream_commit":"0059d4335f8156206f63a35662313385f7ad6d74"},"case_count":4242,"cases_sha256":"245cc5510276b2cf5b5ecbc464d2cde64bf26a5359af49755f92b84f5620b83b","contract":{"absolute_tolerance_native":[1e-12,1e-12,1e-12,1e-12,1e-12,1e-12,1e-12],"action_units":["rad","rad","rad","rad","rad","rad","single_finger_m"],"control_dt_s":0.02,"jaw_rate_m_s":0.05,"joint_order":["joint1","joint2","joint3","joint4","joint5","joint6"],"joint_rate_rad_s":1.5,"limits_native":[[-2.618,2.618],[0.0,3.14],[-2.697,0.0],[-1.832,1.832],[-1.22,1.22],[-3.14,3.14],[0.0,0.035]],"microsteps":20,"reference_kind":"previous_applied_servo_reference","relative_tolerance":0.0,"schema":"dvidia.camera-action-limiter-preflight/v1","timestep_s":0.001},"episode_data_read":false,"gate":"Every 20x7 reference entry agrees within 1e-12 absolute native units; zero relative tolerance; all invalid contracts/states rejected; no skill qualification.","generator":"numpy.default_rng PCG64, float64; all vectors generated before comparisons","near_rate_cases":2048,"schema":"dvidia.camera-action-limiter-preflight-protocol/v1","script_sha256":"39f948ce5100c93fd0f31d3aa3b49f8084fcdafa31ed937db88f2a6b1780fa96","seed":171709,"simulator_import_or_execution":false,"tests_sha256":"f9bd92e5a7be378bab4e1dea55a013a9a1708cc654e02220bf0185de2d982804","training_fits":0,"training_or_confirmation_rollouts":0,"uniform_cases":2048} diff --git a/benchmarks/camera-action-v02-preflight/evidence-20261109/report.json b/benchmarks/camera-action-v02-preflight/evidence-20261109/report.json new file mode 100644 index 0000000..90e335e --- /dev/null +++ b/benchmarks/camera-action-v02-preflight/evidence-20261109/report.json @@ -0,0 +1 @@ +{"analytic_endpoint_bitwise_equal_cases":883,"axes_per_microstep":7,"bitwise_equivalence_claim":false,"case_count":4242,"cases_file_sha256":"5ffc870ddb0b6e7b7187a41558b17b3b47c9a3df479cdd4df949bc814648f766","contrast_may_proceed_to_separately_registered_training":true,"delta_decode_bitwise_equal_cases":883,"limitations":["Synthetic numeric vectors are not robot episodes or a distributional success test.","Float64 arithmetic is compared at a predeclared 1e-12 tolerance, not promised bitwise identity.","Typed reference authority rejects mislabeled fields; this standalone check cannot prove source telemetry provenance.","No policy fitting, model-head initialization equivalence or closed-loop evaluation was performed.","No altered limiter, variable-rate, pulse-actuation or measured-q-relative controller is covered."],"matched_reference_entries_per_comparison":593880,"max_abs_error_by_axis_native":[1.3322676295501878e-15,1.3322676295501878e-15,1.3322676295501878e-15,1.1102230246251565e-15,1.1102230246251565e-15,1.3322676295501878e-15,2.7755575615628914e-17],"max_delta_decode_error_by_axis_native":[1.3322676295501878e-15,1.3322676295501878e-15,1.3322676295501878e-15,1.1102230246251565e-15,1.1102230246251565e-15,1.3322676295501878e-15,2.7755575615628914e-17],"max_replayed_endpoint_error_by_axis_native":[0.0,0.0,0.0,0.0,0.0,0.0,0.0],"measurements_sha256":"3b0f235bdee6f5ef3add2e793fcb4d625f926eb28de1fb6f348dc79df2ad345c","microsteps_per_case":20,"negative_cases":24,"negative_cases_rejected":24,"numerically_equivalent_cases":4242,"physical_robot_ready":false,"protocol_sha256":"55a32578740170841a26bf3c06a36778c8c5e56595cd5003967a2c67dd3fffc1","reference_equivalence_gate_passed":true,"replayed_endpoint_bitwise_equal_cases":4242,"runtime":{"implementation":"CPython","numpy":"2.5.3","platform":"macOS-26.5.2-arm64-arm-64bit","python":"3.12.9"},"schema":"dvidia.camera-action-limiter-preflight-report/v1","scope":"Only constant-target position reference slew over 20 native intervals. Not joint motion, actuator force, contacts, task success or model quality.","skill_improvement_measured":false,"status":"passed","wall_seconds":3.3696212919894606} diff --git a/benchmarks/camera-action-v02-preflight/preflight.py b/benchmarks/camera-action-v02-preflight/preflight.py new file mode 100644 index 0000000..48383b6 --- /dev/null +++ b/benchmarks/camera-action-v02-preflight/preflight.py @@ -0,0 +1,401 @@ +#!/usr/bin/env python3 +"""Numerical reference-limiter preflight; no simulator, fitting or recordings. + +Execute only the two hash-pinned NumPy reference updates extracted from +PiperTaskEnv.step. MuJoCo, renderers and dvidia_training are never imported. +""" +from __future__ import annotations + +import argparse +import ast +from copy import deepcopy +from hashlib import sha256 +import json +import math +from pathlib import Path +import platform +import sys +import time +from types import SimpleNamespace +import xml.etree.ElementTree as ET + +import numpy as np + +BASE_COMMIT = 'ab9082e1ee2b2cc91c7c5fd3f1358727b3789c66' +SOURCE_HASHES = { + 'src/dvidia_training/piper_task.py': 'e66a44a8df4e7a8ee42e4f3866f889f8797cdfb8e2688a146e09b75d2c76664f', + 'src/dvidia_training/piper_imitation.py': '849f66512c58441a240cd20230fcc58691234ddd254c5bbcbfd76abc21b14868', + 'src/dvidia_training/camera_action_model.py': 'e9a9c4d1d0f16fc7c91cac3ca2e6560d0532370ab78a2af5a4ec84425c23932f', + 'src/dvidia_training/camera_action_export.py': '2c4e30587605edc0342150a93430a70ed0559c3ee3eda17d93c5670831370b02', + 'src/dvidia_training/piper_action_capture.py': 'da037b2198cf7d2f3a9aa40fc19a4c0f5cc375a22c5dd75606e2c1856f6efc7f', + 'src/dvidia_training/robot_profiles.lock.json': '4b2ee2ca675aceb2f826983cb3082a3e08e9aa0ff419b23078abcff08ebcc6fe', +} +ORDER = [f'joint{i}' for i in range(1, 7)] +LIMITS = [[-2.618, 2.618], [0., 3.14], [-2.697, 0.], + [-1.832, 1.832], [-1.22, 1.22], [-3.14, 3.14], [0., .035]] +CONTRACT = { + 'schema': 'dvidia.camera-action-limiter-preflight/v1', + 'joint_order': ORDER, + 'action_units': ['rad'] * 6 + ['single_finger_m'], + 'limits_native': LIMITS, + 'reference_kind': 'previous_applied_servo_reference', + 'timestep_s': .001, 'control_dt_s': .02, 'microsteps': 20, + 'joint_rate_rad_s': 1.5, 'jaw_rate_m_s': .05, + 'absolute_tolerance_native': [1e-12] * 7, 'relative_tolerance': 0., +} +EXPECTED_UPDATES = '''self.command_targets += np.clip(targets-self.command_targets, + -self.config.joint_target_rate_rad_s*self.config.timestep, + self.config.joint_target_rate_rad_s*self.config.timestep) +self.command_gripper += float(np.clip(jaw-self.command_gripper, + -self.config.jaw_target_rate_m_s*self.config.timestep, + self.config.jaw_target_rate_m_s*self.config.timestep)) +''' +SEED = 171709 +UNIFORM_CASES = 2048 +NEAR_RATE_CASES = 2048 + + +def canonical(value): + return json.dumps(value, sort_keys=True, separators=(',', ':'), allow_nan=False).encode() + + +def digest(value): + return sha256(canonical(value)).hexdigest() + + +def file_hash(path): + return sha256(Path(path).read_bytes()).hexdigest() + + +def _literal_assignment(tree, name): + for node in tree.body: + if isinstance(node, ast.Assign) and any(isinstance(t, ast.Name) and t.id == name for t in node.targets): + return ast.literal_eval(node.value) + raise ValueError('Missing source constant: ' + name) + + +def _check_contract(value): + if type(value) is not dict or canonical(value) != canonical(CONTRACT): + raise ValueError('The preflight requires unchanged original order, units, limits and rates.') + + +def _numbers(value, length, label): + if type(value) not in (list, tuple) or len(value) != length: + raise ValueError(label + ' requires exactly ' + str(length) + ' numeric values.') + if any(type(v) not in (int, float) or not math.isfinite(v) for v in value): + raise ValueError(label + ' requires finite real numbers, not bool/string/coercion.') + return np.asarray(value, dtype=np.float64) + + +def _action(value): + if type(value) is not dict or set(value) != {'joint_targets_rad', 'gripper_position_m'}: + raise ValueError('Action must contain only six joint targets and a single-finger jaw target.') + joints = _numbers(value['joint_targets_rad'], 6, 'Joint targets') + jaw = _numbers([value['gripper_position_m']], 1, 'Jaw target') + result = np.concatenate((joints, jaw)) + limits = np.asarray(LIMITS) + if np.any(result < limits[:, 0]) or np.any(result > limits[:, 1]): + raise ValueError('Reference/action is outside the unchanged original native limits.') + return result + + +def action(vector): + vector = np.asarray(vector, dtype=np.float64) + return {'joint_targets_rad': vector[:6].tolist(), 'gripper_position_m': float(vector[6])} + + +def reference(vector): + return {'kind': CONTRACT['reference_kind'], 'joint_order': list(ORDER), **action(vector)} + + +def _reference(value): + fields = {'kind', 'joint_order', 'joint_targets_rad', 'gripper_position_m'} + if type(value) is not dict or set(value) != fields: + raise ValueError('Use an explicit preceding applied reference, not measured/future state.') + if value['kind'] != CONTRACT['reference_kind'] or value['joint_order'] != ORDER: + raise ValueError('Wrong reference authority or joint order.') + return _action({k: value[k] for k in ('joint_targets_rad', 'gripper_position_m')}) + + +def load_bindings(repo, piper_xml): + """Hash-pin inputs, inspect constants/XML, then compile only two numeric lines.""" + repo, piper_xml = Path(repo), Path(piper_xml) + for name, expected in SOURCE_HASHES.items(): + if file_hash(repo / name) != expected: + raise ValueError('Frozen source hash differs: ' + name) + source = (repo / 'src/dvidia_training/piper_task.py').read_text() + tree = ast.parse(source) + config = next(n for n in tree.body if isinstance(n, ast.ClassDef) and n.name == 'PiperTaskConfig') + expected = {'timestep': .001, 'control_dt': .02, + 'joint_target_rate_rad_s': 1.5, 'jaw_target_rate_m_s': .05} + defaults = {n.target.id: ast.literal_eval(n.value) for n in config.body + if isinstance(n, ast.AnnAssign) and isinstance(n.target, ast.Name) + and n.target.id in expected} + if any(defaults[k] != v for k, v in expected.items()): + raise ValueError('Original configuration defaults changed.') + imitation = ast.parse((repo / 'src/dvidia_training/piper_imitation.py').read_text()) + if ([list(row) for row in _literal_assignment(imitation, 'JOINT_LIMITS')] != LIMITS[:6] + or _literal_assignment(imitation, 'JAW_MAX_M') != LIMITS[6][1]): + raise ValueError('Original learning/native action bounds changed.') + env = next(n for n in tree.body if isinstance(n, ast.ClassDef) and n.name == 'PiperTaskEnv') + step = next(n for n in env.body if isinstance(n, ast.FunctionDef) and n.name == 'step') + loops = [n for n in ast.walk(step) if isinstance(n, ast.For) and n.body + and isinstance(n.body[0], ast.AugAssign) + and isinstance(n.body[0].target, ast.Attribute) + and n.body[0].target.attr == 'command_targets'] + if len(loops) != 1: + raise ValueError('Expected one original native stepping loop.') + updates = loops[0].body[:2] + expected_tree = ast.parse(EXPECTED_UPDATES) + module = ast.Module(body=updates, type_ignores=[]) + if ast.dump(module, include_attributes=False) != ast.dump(expected_tree, include_attributes=False): + raise ValueError('Original numeric limiter update expressions changed.') + # We do not compile or execute the native step loop, _controls, mj_step or scoring. + compiled = compile(ast.fix_missing_locations(module), '', 'exec') + lock = json.loads((repo / 'src/dvidia_training/robot_profiles.lock.json').read_text()) + profile = next(p for p in lock['profiles'] if p['id'] == 'piper') + pinned = next(f for f in profile['files'] if f['path'] == 'agilex_piper/piper.xml') + if file_hash(piper_xml) != pinned['sha256'] or piper_xml.stat().st_size != pinned['bytes']: + raise ValueError('PiPER XML differs from the existing pinned asset lock.') + xml = ET.fromstring(piper_xml.read_bytes()) + if profile['actuator_names'] != ORDER + ['gripper'] or profile['arm_joint_names'] != ORDER: + raise ValueError('Pinned profile joint/actuator order changed.') + actuators = list(xml.find('actuator')) + if [a.get('name') for a in actuators] != ORDER + ['gripper']: + raise ValueError('Pinned XML actuator order changed.') + joints = {j.get('name'): j for j in xml.findall('.//worldbody//joint')} + xml_limits = [[float(x) for x in joints[n].get('range').split()] for n in ORDER + ['joint7']] + if xml_limits != LIMITS: + raise ValueError('Pinned native joint ranges differ from model action limits.') + # The locked XML gives piper position servos inheritrange=1; finger inherits it. + if xml.find("./default/default[@class='piper']/position").get('inheritrange') != '1': + raise ValueError('Pinned servo joint-range inheritance changed.') + bindings = {'base_source_commit': BASE_COMMIT, 'source_sha256': SOURCE_HASHES, + 'upstream_commit': lock['commit'], 'piper_xml': pinned, + 'limiter_ast_sha256': sha256(ast.dump(module, include_attributes=False).encode()).hexdigest(), + 'limiter_source_lines': [updates[0].lineno, updates[-1].end_lineno], + 'original_defaults': expected, + 'scope': 'Only the two reference updates are executed; XML is parsed without MuJoCo.'} + return compiled, bindings + + +class Limiter: + def __init__(self, compiled): + self.compiled = compiled + + def trajectory(self, previous_reference, target, contract=CONTRACT): + _check_contract(contract) + r, a = _reference(previous_reference), _action(target) + state = SimpleNamespace(command_targets=r[:6].copy(), command_gripper=float(r[6]), + config=SimpleNamespace(timestep=.001, control_dt=.02, + joint_target_rate_rad_s=1.5, jaw_target_rate_m_s=.05)) + scope = {'self': state, 'targets': a[:6], 'jaw': float(a[6]), 'np': np, 'float': float} + result = [] + for _ in range(20): + exec(self.compiled, {'__builtins__': {}}, scope) + result.append(np.concatenate((state.command_targets.copy(), [state.command_gripper]))) + return np.asarray(result, dtype=np.float64) + + def endpoint(self, previous_reference, target, contract=CONTRACT): + """Closed-form P; no rollout, measured joints, object truth or teacher lookup.""" + _check_contract(contract) + r, a = _reference(previous_reference), _action(target) + return r + np.clip(a-r, -interval_allowance(), interval_allowance()) + + +def interval_allowance(): + return np.asarray([1.5] * 6 + [.05], dtype=np.float64) * .02 + + +def cases(): + """Fixed synthetic numerical training-development vectors, not scene episodes.""" + limits = np.asarray(LIMITS) + low, high = limits[:, 0], limits[:, 1] + middle = (low+high)/2. + rows = [] + + def add(name, r, a, group): + rows.append({'case_id': name, 'group': group, 'usage': 'numerical_training_development_only', + 'previous_reference': reference(r), 'teacher_target': action(a)}) + + for name, r, a in [('hold_low', low, low), ('hold_high', high, high), + ('hold_middle', middle, middle), ('all_increase', low, high), + ('all_decrease', high, low), + ('mixed_directions', np.where(np.arange(7) % 2, low, high), middle)]: + add(name, r, a, 'explicit_bounds') + tick = interval_allowance()/20. + for axis in range(7): + for sign in (-1., 1.): + for magnitude in (0., .5, 1., 2., 19., 20., 20.5, 21., 40.): + a = middle.copy(); a[axis] += sign*tick[axis]*magnitude + add(f'axis{axis}_sign{int(sign)}_ticks{magnitude:g}', middle, a, 'tick_boundaries') + for bound, endpoint in [('low', low[axis]), ('high', high[axis])]: + r, a = middle.copy(), middle.copy() + r[axis] = np.nextafter(endpoint, middle[axis]); a[axis] = endpoint + add(f'axis{axis}_one_ulp_from_{bound}', r, a, 'ulp_boundaries') + rng = np.random.default_rng(SEED) + for i in range(UNIFORM_CASES): + add(f'uniform_{i:04}', rng.uniform(low, high), rng.uniform(low, high), 'uniform_bounded') + for i in range(NEAR_RATE_CASES): + r = rng.uniform(low, high) + a = np.clip(r+rng.uniform(-1.25, 1.25, 7)*interval_allowance(), low, high) + add(f'near_rate_{i:04}', r, a, 'near_interval_allowance') + return rows + + +def negative_cases(limiter): + midpoint = np.asarray(LIMITS).mean(axis=1) + ref, target = reference(midpoint), action(midpoint) + variants = [] + def add(name, ref_value=ref, target_value=target, contract=CONTRACT): + variants.append((name, deepcopy(ref_value), deepcopy(target_value), deepcopy(contract))) + for field, value in [('joint_rate_rad_s', 1.6), ('jaw_rate_m_s', .06), + ('timestep_s', .002), ('microsteps', 10), ('control_dt_s', .04)]: + c = deepcopy(CONTRACT); c[field] = value; add('changed_'+field, contract=c) + c = deepcopy(CONTRACT); c['limits_native'][0][0] -= .01; add('changed_joint_limit', contract=c) + c = deepcopy(CONTRACT); c['limits_native'][6][1] += .01; add('changed_jaw_limit', contract=c) + c = deepcopy(CONTRACT); c['joint_order'][0:2] = c['joint_order'][1::-1]; add('changed_contract_order', contract=c) + r = deepcopy(ref); r['joint_order'][0:2] = r['joint_order'][1::-1]; add('changed_reference_order', ref_value=r) + for kind in ('measured_joint_position', 'future_applied_reference', 'teacher_query_target'): + r = deepcopy(ref); r['kind'] = kind; add('wrong_state_'+kind, ref_value=r) + r = deepcopy(ref); r['measured_joint_position_rad'] = midpoint[:6].tolist(); add('extra_measured_state', ref_value=r) + r = deepcopy(ref); del r['kind']; add('missing_reference_authority', ref_value=r) + for name, value in [('nan', float('nan')), ('infinity', float('inf')), ('bool', True), ('string', '0')]: + a = deepcopy(target); a['joint_targets_rad'][0] = value; add('invalid_target_'+name, target_value=a) + a = deepcopy(target); a['joint_targets_rad'] = a['joint_targets_rad'][:-1]; add('target_length', target_value=a) + a = deepcopy(target); a['joint_targets_rad'][0] = LIMITS[0][1]+1e-6; add('target_joint_bound', target_value=a) + for jaw in (-1e-6, .035001): + a = deepcopy(target); a['gripper_position_m'] = jaw; add('target_jaw_bound_'+str(jaw), target_value=a) + r = deepcopy(ref); r['joint_targets_rad'][0] = LIMITS[0][0]-1e-6; add('reference_joint_bound', ref_value=r) + r = deepcopy(ref); r['gripper_position_m'] = -.001; add('reference_jaw_bound', ref_value=r) + results = [] + for name, r, a, c in variants: + rejected = [] + for operation in (limiter.trajectory, limiter.endpoint): + try: + operation(r, a, c) + rejected.append(False) + except (ValueError, TypeError, OverflowError): + rejected.append(True) + results.append({'case_id': name, 'original_and_projection_rejected': all(rejected)}) + return results + + +def compare_case(limiter, row): + r, a = row['previous_reference'], row['teacher_target'] + original = limiter.trajectory(r, a) + endpoint = limiter.endpoint(r, a) + projected = limiter.trajectory(r, action(endpoint)) + exact_endpoint = limiter.trajectory(r, action(original[-1])) + error = np.abs(projected-original) + exact_error = np.abs(exact_endpoint-original) + limits = np.asarray(LIMITS) + allowance = interval_allowance() + delta = (endpoint-_reference(r))/allowance + # Cdelta decode is tested here; no learned Cdelta or Cabs model exists yet. + decoded = _reference(r)+delta*allowance + decoded_trajectory = limiter.trajectory(r, action(decoded)) + decoded_error = np.abs(decoded_trajectory-original) + within = bool(np.all(projected >= limits[:, 0]) and np.all(projected <= limits[:, 1])) + tolerance = np.asarray(CONTRACT['absolute_tolerance_native']) + return {'case_id': row['case_id'], 'group': row['group'], + 'max_abs_error_by_axis_native': error.max(axis=0).tolist(), + 'max_exact_endpoint_error_by_axis_native': exact_error.max(axis=0).tolist(), + 'max_delta_decode_error_by_axis_native': decoded_error.max(axis=0).tolist(), + 'bitwise_equal_analytic_endpoint': original.tobytes() == projected.tobytes(), + 'bitwise_equal_replayed_endpoint': original.tobytes() == exact_endpoint.tobytes(), + 'bitwise_equal_delta_decode': original.tobytes() == decoded_trajectory.tobytes(), + 'within_native_limits': within, + 'delta_within_unit_interval': bool(np.all(np.abs(delta) <= 1.+1e-12)), + 'passed': bool(np.all(error <= tolerance) and np.all(exact_error <= tolerance) + and np.all(decoded_error <= tolerance) and within + and np.all(np.abs(delta) <= 1.+1e-12))} + + +def _write_new(path, value): + with Path(path).open('xb') as stream: + stream.write(canonical(value)+b'\n') + + +def run(repo, piper_xml, output): + compiled, bindings = load_bindings(repo, piper_xml) + output = Path(output) + if output.exists(): + raise ValueError('Evidence output must be new; previous outcomes are never overwritten.') + script = Path(__file__) + test_path = script.with_name('test_preflight.py') + rows = cases() + protocol = {'schema': 'dvidia.camera-action-limiter-preflight-protocol/v1', + 'contract': CONTRACT, 'bindings': bindings, 'seed': SEED, + 'uniform_cases': UNIFORM_CASES, 'near_rate_cases': NEAR_RATE_CASES, + 'case_count': len(rows), 'cases_sha256': digest(rows), + 'generator': 'numpy.default_rng PCG64, float64; all vectors generated before comparisons', + 'script_sha256': file_hash(script), 'tests_sha256': file_hash(test_path), + 'episode_data_read': False, 'training_or_confirmation_rollouts': 0, + 'training_fits': 0, 'simulator_import_or_execution': False, + 'gate': 'Every 20x7 reference entry agrees within 1e-12 absolute native units; ' + 'zero relative tolerance; all invalid contracts/states rejected; no skill qualification.'} + output.mkdir(parents=True) + _write_new(output/'cases.json', rows) + _write_new(output/'protocol.json', protocol) + began = time.perf_counter() + limiter = Limiter(compiled) + results = [compare_case(limiter, row) for row in rows] + negatives = negative_cases(limiter) + max_error = np.max([r['max_abs_error_by_axis_native'] for r in results], axis=0) + delta_error = np.max([r['max_delta_decode_error_by_axis_native'] for r in results], axis=0) + exact_error = np.max([r['max_exact_endpoint_error_by_axis_native'] for r in results], axis=0) + allowed = all(r['passed'] for r in results) and all(r['original_and_projection_rejected'] for r in negatives) + _write_new(output/'measurements.json', {'cases': results, 'negative_cases': negatives}) + report = {'schema': 'dvidia.camera-action-limiter-preflight-report/v1', + 'status': 'passed' if allowed else 'blocked', + 'reference_equivalence_gate_passed': allowed, + 'contrast_may_proceed_to_separately_registered_training': allowed, + 'bitwise_equivalence_claim': False, + 'protocol_sha256': file_hash(output/'protocol.json'), + 'cases_file_sha256': file_hash(output/'cases.json'), + 'measurements_sha256': file_hash(output/'measurements.json'), + 'case_count': len(rows), 'microsteps_per_case': 20, 'axes_per_microstep': 7, + 'matched_reference_entries_per_comparison': len(rows)*20*7, + 'numerically_equivalent_cases': sum(r['passed'] for r in results), + 'analytic_endpoint_bitwise_equal_cases': sum(r['bitwise_equal_analytic_endpoint'] for r in results), + 'replayed_endpoint_bitwise_equal_cases': sum(r['bitwise_equal_replayed_endpoint'] for r in results), + 'delta_decode_bitwise_equal_cases': sum(r['bitwise_equal_delta_decode'] for r in results), + 'max_abs_error_by_axis_native': max_error.tolist(), + 'max_delta_decode_error_by_axis_native': delta_error.tolist(), + 'max_replayed_endpoint_error_by_axis_native': exact_error.tolist(), + 'negative_cases': len(negatives), + 'negative_cases_rejected': sum(r['original_and_projection_rejected'] for r in negatives), + 'wall_seconds': time.perf_counter()-began, + 'runtime': {'python': platform.python_version(), 'numpy': np.__version__, + 'platform': platform.platform(), 'implementation': platform.python_implementation()}, + 'physical_robot_ready': False, 'skill_improvement_measured': False, + 'scope': 'Only constant-target position reference slew over 20 native intervals. ' + 'Not joint motion, actuator force, contacts, task success or model quality.', + 'limitations': ['Synthetic numeric vectors are not robot episodes or a distributional success test.', + 'Float64 arithmetic is compared at a predeclared 1e-12 tolerance, not promised bitwise identity.', + 'Typed reference authority rejects mislabeled fields; this standalone check cannot prove source telemetry provenance.', + 'No policy fitting, model-head initialization equivalence or closed-loop evaluation was performed.', + 'No altered limiter, variable-rate, pulse-actuation or measured-q-relative controller is covered.']} + _write_new(output/'report.json', report) + return report + + +def main(): + parser = argparse.ArgumentParser(description=__doc__) + parser.add_argument('--repo', type=Path, default=Path(__file__).resolve().parents[2]) + parser.add_argument('--piper-xml', type=Path, required=True) + parser.add_argument('--output', type=Path, required=True) + args = parser.parse_args() + try: + report = run(args.repo, args.piper_xml, args.output) + except (ValueError, OSError, StopIteration, KeyError) as exc: + print(json.dumps({'status': 'blocked', 'error': str(exc)}), file=sys.stderr) + return 2 + print(json.dumps({k: report[k] for k in ('status', 'case_count', 'numerically_equivalent_cases', + 'negative_cases_rejected', 'wall_seconds')}, indent=2)) + return 0 if report['reference_equivalence_gate_passed'] else 1 + + +if __name__ == '__main__': + raise SystemExit(main()) diff --git a/benchmarks/camera-action-v02-preflight/test_preflight.py b/benchmarks/camera-action-v02-preflight/test_preflight.py new file mode 100644 index 0000000..5c190f0 --- /dev/null +++ b/benchmarks/camera-action-v02-preflight/test_preflight.py @@ -0,0 +1,177 @@ +"""Pure numeric contract tests; no native simulation or model fitting. + +Set DVIDIA_PREFLIGHT_PIPER_XML to the existing hash-pinned piper.xml to run +source/XML binding tests too. Those tests do not load meshes or MuJoCo. +""" +from copy import deepcopy +import importlib.util +import json +import os +from pathlib import Path +import shutil +import sys +import tempfile +import unittest + +import numpy as np + +HERE = Path(__file__).resolve().parent +spec = importlib.util.spec_from_file_location('camera_action_v02_numerical_preflight', HERE/'preflight.py') +p = importlib.util.module_from_spec(spec) +spec.loader.exec_module(p) +REPO = HERE.parents[1] + + +class NumericalTests(unittest.TestCase): + def setUp(self): + import ast + self.limiter = p.Limiter(compile(ast.parse(p.EXPECTED_UPDATES), '', 'exec')) + self.middle = np.asarray(p.LIMITS).mean(axis=1) + self.reference = p.reference(self.middle) + self.target = p.action(self.middle) + + def test_stationary_reference_is_stationary(self): + actual = self.limiter.trajectory(self.reference, self.target) + np.testing.assert_array_equal(actual, np.repeat(self.middle[None], 20, axis=0)) + + def test_twenty_monotone_reference_steps_keep_original_rates(self): + target = p.action(np.asarray(p.LIMITS)[:, 1]) + actual = self.limiter.trajectory(self.reference, target) + expected = self.middle[None] + np.arange(1, 21)[:, None]*np.asarray([.0015]*6+[.00005]) + np.testing.assert_allclose(actual, expected, atol=1e-12, rtol=0.) + np.testing.assert_allclose(actual[-1]-self.middle, [.03]*6+[.001], atol=1e-12, rtol=0.) + + def test_inside_one_microstep_target_reaches_and_holds(self): + target = p.action(self.middle+np.asarray([.0005]*6+[.00001])) + actual = self.limiter.trajectory(self.reference, target) + np.testing.assert_allclose(actual, np.repeat(p._action(target)[None], 20, axis=0), atol=1e-12, rtol=0.) + + def test_both_bound_directions_and_mixed_axes_equivalent(self): + for row in p.cases()[:146]: + with self.subTest(case=row['case_id']): + self.assertTrue(p.compare_case(self.limiter, row)['passed']) + + def test_generated_vectors_are_deterministic_and_separate_from_episodes(self): + first, second = p.cases(), p.cases() + self.assertEqual(p.digest(first), p.digest(second)) + self.assertEqual(len(first), 4242) + self.assertEqual(len({r['case_id'] for r in first}), len(first)) + self.assertTrue(all(r['usage'] == 'numerical_training_development_only' for r in first)) + for row in first: + p._reference(row['previous_reference']); p._action(row['teacher_target']) + + def test_random_cases_include_target_reached_and_rate_limited(self): + for row in p.cases()[146:166] + p.cases()[-20:]: + self.assertTrue(p.compare_case(self.limiter, row)['passed']) + + def test_all_negative_contract_and_authority_cases_rejected(self): + negatives = p.negative_cases(self.limiter) + self.assertGreaterEqual(len(negatives), 24) + self.assertTrue(all(r['original_and_projection_rejected'] for r in negatives)) + + def test_authority_is_previous_applied_reference_not_measured_position(self): + target = p.action(np.asarray(p.LIMITS)[:, 1]) + altered = self.middle.copy(); altered[0] += .3 + a = self.limiter.trajectory(self.reference, target) + b = self.limiter.trajectory(p.reference(altered), target) + self.assertGreater(float(np.max(np.abs(a-b))), .29) + measured = deepcopy(self.reference); measured['kind'] = 'measured_joint_position' + with self.assertRaises(ValueError): + self.limiter.trajectory(measured, target) + + def test_future_or_teacher_reference_cannot_be_substituted(self): + for authority in ('future_applied_reference', 'teacher_query_target'): + ref = deepcopy(self.reference); ref['kind'] = authority + with self.assertRaises(ValueError): + self.limiter.endpoint(ref, self.target) + + def test_no_silent_joint_reordering(self): + ref = deepcopy(self.reference); ref['joint_order'] = ref['joint_order'][::-1] + with self.assertRaises(ValueError): + self.limiter.trajectory(ref, self.target) + + def test_no_extra_truth_or_reference_inputs(self): + for field in ('reference.action', 'native_object_position', 'teacher_phase', 'future_observation'): + ref = deepcopy(self.reference); ref[field] = 0 + with self.assertRaises(ValueError): + self.limiter.endpoint(ref, self.target) + + def test_no_silent_clipping_of_invalid_targets(self): + target = deepcopy(self.target); target['gripper_position_m'] = .04 + with self.assertRaises(ValueError): + self.limiter.endpoint(self.reference, target) + + def test_delta_decode_uses_previous_reference_and_physical_allowance(self): + target = p.action(np.asarray(p.LIMITS)[:, 0]) + endpoint = self.limiter.endpoint(self.reference, target) + delta = (endpoint-self.middle)/p.interval_allowance() + np.testing.assert_allclose(delta, [-1.]*7, atol=1e-12, rtol=0.) + decoded = self.middle+delta*p.interval_allowance() + np.testing.assert_allclose(decoded, endpoint, atol=1e-12, rtol=0.) + + def test_microstep_history_not_only_endpoint_compared(self): + class ReorderedLimiter(p.Limiter): + calls = 0 + def trajectory(self, *args, **kwargs): + result = super().trajectory(*args, **kwargs) + self.calls += 1 + if self.calls == 2: + result[[0, 1]] = result[[1, 0]] + return result + mutant = ReorderedLimiter(self.limiter.compiled) + row = p.cases()[3] + result = p.compare_case(mutant, row) + self.assertFalse(result['passed']) + self.assertGreater(max(result['max_abs_error_by_axis_native']), 1e-12) + + def test_inputs_are_not_mutated(self): + original = deepcopy((self.reference, self.target, p.CONTRACT)) + self.limiter.trajectory(self.reference, self.target) + self.limiter.endpoint(self.reference, self.target) + self.assertEqual((self.reference, self.target, p.CONTRACT), original) + + def test_no_native_import(self): + self.assertFalse(any(n == 'mujoco' or n.startswith('dvidia_training') for n in sys.modules)) + + +@unittest.skipUnless(os.environ.get('DVIDIA_PREFLIGHT_PIPER_XML'), 'Set hash-pinned DVIDIA_PREFLIGHT_PIPER_XML for source/XML tests.') +class SourceBindingTests(unittest.TestCase): + def setUp(self): + self.xml = Path(os.environ['DVIDIA_PREFLIGHT_PIPER_XML']) + + def test_original_sources_and_xml_bind(self): + compiled, bindings = p.load_bindings(REPO, self.xml) + self.assertEqual(bindings['base_source_commit'], p.BASE_COMMIT) + self.assertEqual(bindings['source_sha256'], p.SOURCE_HASHES) + self.assertEqual(bindings['limiter_source_lines'], [307, 312]) + self.assertTrue(p.compare_case(p.Limiter(compiled), p.cases()[3])['passed']) + + def test_changed_xml_rejected_before_any_step(self): + with tempfile.TemporaryDirectory() as temp: + xml = Path(temp)/'piper.xml' + xml.write_bytes(self.xml.read_bytes().replace(b'joint1', b'joint9', 1)) + with self.assertRaisesRegex(ValueError, 'XML differs'): + p.load_bindings(REPO, xml) + + def test_changed_native_limiter_source_rejected(self): + with tempfile.TemporaryDirectory() as temp: + root = Path(temp) + for name in p.SOURCE_HASHES: + target = root/name; target.parent.mkdir(parents=True, exist_ok=True) + shutil.copyfile(REPO/name, target) + target = root/'src/dvidia_training/piper_task.py' + target.write_text(target.read_text().replace('joint_target_rate_rad_s: float = 1.5', 'joint_target_rate_rad_s: float = 1.6')) + with self.assertRaisesRegex(ValueError, 'Frozen source hash differs'): + p.load_bindings(root, self.xml) + + def test_existing_output_refused_without_rewrite(self): + with tempfile.TemporaryDirectory() as temp: + output = Path(temp)/'evidence'; output.mkdir() + sentinel = output/'report.json'; sentinel.write_text('preserved') + with self.assertRaisesRegex(ValueError, 'output must be new'): + p.run(REPO, self.xml, output) + self.assertEqual(sentinel.read_text(), 'preserved') + + +if __name__ == '__main__': + unittest.main() diff --git a/benchmarks/camera-action-v02-preflight/tests-20261109.log b/benchmarks/camera-action-v02-preflight/tests-20261109.log new file mode 100644 index 0000000..547cab7 --- /dev/null +++ b/benchmarks/camera-action-v02-preflight/tests-20261109.log @@ -0,0 +1,25 @@ +test_all_negative_contract_and_authority_cases_rejected (test_preflight.NumericalTests.test_all_negative_contract_and_authority_cases_rejected) ... ok +test_authority_is_previous_applied_reference_not_measured_position (test_preflight.NumericalTests.test_authority_is_previous_applied_reference_not_measured_position) ... ok +test_both_bound_directions_and_mixed_axes_equivalent (test_preflight.NumericalTests.test_both_bound_directions_and_mixed_axes_equivalent) ... ok +test_delta_decode_uses_previous_reference_and_physical_allowance (test_preflight.NumericalTests.test_delta_decode_uses_previous_reference_and_physical_allowance) ... ok +test_future_or_teacher_reference_cannot_be_substituted (test_preflight.NumericalTests.test_future_or_teacher_reference_cannot_be_substituted) ... ok +test_generated_vectors_are_deterministic_and_separate_from_episodes (test_preflight.NumericalTests.test_generated_vectors_are_deterministic_and_separate_from_episodes) ... ok +test_inputs_are_not_mutated (test_preflight.NumericalTests.test_inputs_are_not_mutated) ... ok +test_inside_one_microstep_target_reaches_and_holds (test_preflight.NumericalTests.test_inside_one_microstep_target_reaches_and_holds) ... ok +test_microstep_history_not_only_endpoint_compared (test_preflight.NumericalTests.test_microstep_history_not_only_endpoint_compared) ... ok +test_no_extra_truth_or_reference_inputs (test_preflight.NumericalTests.test_no_extra_truth_or_reference_inputs) ... ok +test_no_native_import (test_preflight.NumericalTests.test_no_native_import) ... ok +test_no_silent_clipping_of_invalid_targets (test_preflight.NumericalTests.test_no_silent_clipping_of_invalid_targets) ... ok +test_no_silent_joint_reordering (test_preflight.NumericalTests.test_no_silent_joint_reordering) ... ok +test_random_cases_include_target_reached_and_rate_limited (test_preflight.NumericalTests.test_random_cases_include_target_reached_and_rate_limited) ... ok +test_stationary_reference_is_stationary (test_preflight.NumericalTests.test_stationary_reference_is_stationary) ... ok +test_twenty_monotone_reference_steps_keep_original_rates (test_preflight.NumericalTests.test_twenty_monotone_reference_steps_keep_original_rates) ... ok +test_changed_native_limiter_source_rejected (test_preflight.SourceBindingTests.test_changed_native_limiter_source_rejected) ... ok +test_changed_xml_rejected_before_any_step (test_preflight.SourceBindingTests.test_changed_xml_rejected_before_any_step) ... ok +test_existing_output_refused_without_rewrite (test_preflight.SourceBindingTests.test_existing_output_refused_without_rewrite) ... ok +test_original_sources_and_xml_bind (test_preflight.SourceBindingTests.test_original_sources_and_xml_bind) ... ok + +---------------------------------------------------------------------- +Ran 20 tests in 0.690s + +OK diff --git a/benchmarks/camera-action-v02-preflight/tests-source-parser-development.log b/benchmarks/camera-action-v02-preflight/tests-source-parser-development.log new file mode 100644 index 0000000..de2c451 --- /dev/null +++ b/benchmarks/camera-action-v02-preflight/tests-source-parser-development.log @@ -0,0 +1,64 @@ +Development-only failing test log; local checkout path redacted. Corrected before the sealed numerical run. + +test_all_negative_contract_and_authority_cases_rejected (test_preflight.NumericalTests.test_all_negative_contract_and_authority_cases_rejected) ... ok +test_authority_is_previous_applied_reference_not_measured_position (test_preflight.NumericalTests.test_authority_is_previous_applied_reference_not_measured_position) ... ok +test_both_bound_directions_and_mixed_axes_equivalent (test_preflight.NumericalTests.test_both_bound_directions_and_mixed_axes_equivalent) ... ok +test_delta_decode_uses_previous_reference_and_physical_allowance (test_preflight.NumericalTests.test_delta_decode_uses_previous_reference_and_physical_allowance) ... ok +test_future_or_teacher_reference_cannot_be_substituted (test_preflight.NumericalTests.test_future_or_teacher_reference_cannot_be_substituted) ... ok +test_generated_vectors_are_deterministic_and_separate_from_episodes (test_preflight.NumericalTests.test_generated_vectors_are_deterministic_and_separate_from_episodes) ... ok +test_inputs_are_not_mutated (test_preflight.NumericalTests.test_inputs_are_not_mutated) ... ok +test_inside_one_microstep_target_reaches_and_holds (test_preflight.NumericalTests.test_inside_one_microstep_target_reaches_and_holds) ... ok +test_microstep_history_not_only_endpoint_compared (test_preflight.NumericalTests.test_microstep_history_not_only_endpoint_compared) ... ok +test_no_extra_truth_or_reference_inputs (test_preflight.NumericalTests.test_no_extra_truth_or_reference_inputs) ... ok +test_no_native_import (test_preflight.NumericalTests.test_no_native_import) ... ok +test_no_silent_clipping_of_invalid_targets (test_preflight.NumericalTests.test_no_silent_clipping_of_invalid_targets) ... ok +test_no_silent_joint_reordering (test_preflight.NumericalTests.test_no_silent_joint_reordering) ... ok +test_random_cases_include_target_reached_and_rate_limited (test_preflight.NumericalTests.test_random_cases_include_target_reached_and_rate_limited) ... ok +test_stationary_reference_is_stationary (test_preflight.NumericalTests.test_stationary_reference_is_stationary) ... ok +test_twenty_monotone_reference_steps_keep_original_rates (test_preflight.NumericalTests.test_twenty_monotone_reference_steps_keep_original_rates) ... ok +test_changed_native_limiter_source_rejected (test_preflight.SourceBindingTests.test_changed_native_limiter_source_rejected) ... ok +test_changed_xml_rejected_before_any_step (test_preflight.SourceBindingTests.test_changed_xml_rejected_before_any_step) ... FAIL +test_existing_output_refused_without_rewrite (test_preflight.SourceBindingTests.test_existing_output_refused_without_rewrite) ... FAIL +test_original_sources_and_xml_bind (test_preflight.SourceBindingTests.test_original_sources_and_xml_bind) ... ERROR + +====================================================================== +ERROR: test_original_sources_and_xml_bind (test_preflight.SourceBindingTests.test_original_sources_and_xml_bind) +---------------------------------------------------------------------- +Traceback (most recent call last): + File "/benchmarks/camera-action-v02-preflight/test_preflight.py", line 143, in test_original_sources_and_xml_bind + compiled, bindings = p.load_bindings(REPO, self.xml) + ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + File "/benchmarks/camera-action-v02-preflight/preflight.py", line 144, in load_bindings + raise ValueError('Expected one original native stepping loop.') +ValueError: Expected one original native stepping loop. + +====================================================================== +FAIL: test_changed_xml_rejected_before_any_step (test_preflight.SourceBindingTests.test_changed_xml_rejected_before_any_step) +---------------------------------------------------------------------- +ValueError: Expected one original native stepping loop. + +During handling of the above exception, another exception occurred: + +Traceback (most recent call last): + File "/benchmarks/camera-action-v02-preflight/test_preflight.py", line 153, in test_changed_xml_rejected_before_any_step + with self.assertRaisesRegex(ValueError, 'XML differs'): + ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +AssertionError: "XML differs" does not match "Expected one original native stepping loop." + +====================================================================== +FAIL: test_existing_output_refused_without_rewrite (test_preflight.SourceBindingTests.test_existing_output_refused_without_rewrite) +---------------------------------------------------------------------- +ValueError: Expected one original native stepping loop. + +During handling of the above exception, another exception occurred: + +Traceback (most recent call last): + File "/benchmarks/camera-action-v02-preflight/test_preflight.py", line 171, in test_existing_output_refused_without_rewrite + with self.assertRaisesRegex(ValueError, 'output must be new'): + ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +AssertionError: "output must be new" does not match "Expected one original native stepping loop." + +---------------------------------------------------------------------- +Ran 20 tests in 0.657s + +FAILED (failures=2, errors=1) diff --git a/docs/camera-action-export-cache-v01.md b/docs/camera-action-export-cache-v01.md new file mode 100644 index 0000000..d63577e --- /dev/null +++ b/docs/camera-action-export-cache-v01.md @@ -0,0 +1,89 @@ +# Verified camera-action export cache v0.1 + +Repeated local training preparation can reuse the exact derived arrays from a strict export instead of rereading thousands of RGB-D and sidecar files. This optional cache preserves the existing features, issued or separately queried action labels, missing-value masks, groups and provenance. It does not change the frozen v0.1 model, study, task scorer or result. No training or native rollout was run for this change. + +The interface is `dvidia-train cache`; `python -m dvidia_training.camera_action_cache` remains available. Existing `dvidia-train robot` behavior remains unchanged; a future, separately registered study must choose this cache explicitly. + +## Build once, retain the pins independently + +Install the checkout with the existing NumPy dependency. The study must have sealed, complete demonstration/correction stages, an exact registered runtime and no worker lock. Supply its independently retained protocol SHA-256. Use a fresh output directory outside the study; the parent must already exist. + +```sh +dvidia-train cache build /path/to/sealed-study /path/to/cache \ + --protocol-sha256 APPROVED_PROTOCOL_SHA256 \ + --split train --stage demonstrations > /path/to/trusted-run-record/cache-pins.json +``` + +By default this selects every eligible episode in that split, in protocol order. Repeat `--attempt ID` to select an explicit ordered subset; an ineligible, duplicate or reordered ID is rejected. Demonstrations require complete episodes with a bound initial camera and successful authored-teacher outcome, matching the unchanged study exporter. Corrections require `--stage corrections --split train`, use separate teacher-query suggestions as labels, and retain actual control authority in provenance. `--blind` uses the same exporter with its existing feedback masking. Development demonstrations can be cached separately using `--split development`; confirmation cannot be exported through this interface. + +The build calls the original strict exporter, checks source and episode/stage seals, and writes only: + +- `features.npy`: finite C-order float32 features, including the existing availability masks and ages. +- `targets.npy`: finite C-order float64 absolute targets within the original joint/jaw bounds. +- `manifest.json`: exact protocol, split, stage and ordered episode identities; provenance; array shapes, dtypes, hashes and dataset identity; implementation and feature-contract hashes. + +The single-episode exporter already produces float32 features. The existing multi-episode combiner promotes them to float64; the cache stores those originally float32 values as float32 again, preserving numeric values and the model dataset digest exactly. It does not promise identical ndarray dtype or NPY storage bytes to a combined strict export. Targets stay float64. + +Files are linked atomically, their writable temporary names are removed, and their complete targets are sealed read-only; this ordering permits cleanup on Windows. The manifest is linked last. An interrupted directory is incomplete and is never overwritten or treated as a cache hit. Cache size is bounded to 128,000 samples. Before writing, the builder requires enough space for the bounded output plus a 30 GiB reserve. It does not delete recordings or allocate cloud resources. + +The returned manifest, protocol, split and source pins must be kept in an independently trusted run record. A checksum stored only beside untrusted data is not authorization. Changing both a cache and its own self-reported hashes cannot satisfy the original caller pins. Replacing the independent pins with values from the changed cache defeats that guarantee. + +## Load or inspect with explicit expectations + +```sh +dvidia-train cache inspect /path/to/cache \ + --manifest-sha256 APPROVED_MANIFEST_SHA256 \ + --protocol-sha256 APPROVED_PROTOCOL_SHA256 \ + --split train --source-sha256 APPROVED_SOURCE_SHA256 +``` + +`inspect` and `load` perform the same full derived-cache integrity check. Neither starts or authorizes training. The caller remains responsible for choosing eligible data and keeping training/development group sets disjoint in a newly registered experiment. The `source` command reports the current exact implementation identity; it cannot bless a cache with a different source identity. + +For Python callers: + +```python +from dvidia_training.camera_action_cache import load_cache + +dataset = load_cache( + "/path/to/cache", + expected_manifest_sha256=approved_manifest_sha256, + expected_protocol_sha256=approved_protocol_sha256, + expected_split="train", + expected_source_sha256=approved_source_sha256, +) +``` + +`dataset` has the unchanged mask-aware exporter format and is suitable for explicit downstream selection. Returned arrays are read-only. Loading verifies every cached byte, dtype, shape, finite-value bound, mask, causal episode row order and dataset hash. Unknown files, symlinks, hard links, changed/reordered/truncated arrays, split mismatches, code mismatches and wrong caller pins are rejected. NPY loading forbids pickle and bounds headers. + +**A cache hit does not reverify raw recordings.** It verifies the derived snapshot that was created when the strict exporter checked those recordings. Raw source bytes can only be assumed unchanged if the caller preserves them immutably after that verification; build/load checks are not a producer signature, exclusive filesystem lock or hardware attestation. Rebuild from raw recordings when fresh raw-source validation is required. Source/feature-code changes invalidate prior caches automatically. + +## Measured local preparation cost + +The measured case was the first protocol-ordered training demonstration, `train-00-goal0-teacher`: 1,000 control samples. The original episode contains 6,011 files totaling 197,398,789 bytes. The derived cache is 1,137,058 bytes; raw data remains intact. + +| Operation | Wall time | +|---|---:| +| Unchanged strict export | 1.636 s | +| Strict export plus fresh cache construction | 1.053 s | +| Verified cache load 1 | 2.952 ms | +| Verified cache load 2 | 2.831 ms | +| Verified cache load 3 | 3.214 ms | + +Median validated load was 2.952 ms, about 554× faster than this one measured strict export. Features, targets, groups, provenance and the complete dataset digest matched exactly on all three loads. The build also exports strictly; its shorter observed time is a warm-cache/order effect, not an optimized strict exporter. + +This was one episode on a shared arm64 macOS laptop, Python 3.12.9 and NumPy 2.5.3, with existing filesystem caches and no dedicated CPU reservation. CPU branding/memory sysctl metadata was unavailable in the sandbox. Process peak RSS was 163,463,168 bytes, including strict export and construction; it is not isolated cache memory. Timing includes validation/source hashes and excludes Python imports; explicit equality comparisons follow each timed load. The first reporter attempt reached cache creation and equality checks but failed on restricted host metadata; that directory is retained. The corrected reporter produced the [prior-source measurement](../benchmarks/camera-action-export-cache-v01/results-prior-source.json), bound to cache module `ad79c142b51798281c3f2ce0645662e24da8a21e778ae7785ce9c2c44102c185`. Review then corrected Windows cleanup ordering: the temporary hard-link name must stay writable until it is removed. The [current measurement](../benchmarks/camera-action-export-cache-v01/results.json) reran the same first training episode in a fresh directory, bound to module `9191f2eb9f96bd09d4f711c31966a583bd938853a874e6018f8ddebfb0bc00d8`. All prior artifacts are preserved. These are three disclosed data-preparation attempts, not a controlled speed comparison between implementations. No benchmark scenes were replaced, no models fitted and no native simulation ran. + +A fresh offline `0.1.3.dev5` wheel install outside the checkout matched the current benchmark source identity, loaded/inspected its cache with independent pins, rejected the wrong split and preserved the existing robot and footage CLI help. The focused CLI/cache/export suite passed 25 tests on macOS, including the portable cleanup order and original low-disk refusal. CPU CI includes the cache tests on Ubuntu, macOS and Windows; this local verification does not substitute for a Windows CI run. + +This measures repeated data preparation only. It is not evidence of faster policy inference, better grip/placement success, whole-study throughput or physical-arm readiness. The v0.1 learned result remains 5/64 strict unseen placements and unqualified. + +## Reproduce the bounded measurement + +```sh +python benchmarks/camera-action-export-cache-v01/benchmark.py \ + /path/to/sealed-study /path/to/fresh-proof-directory \ + --protocol-sha256 APPROVED_PROTOCOL_SHA256 +python -m unittest tests.test_camera_action_cache tests.test_camera_cache_cli tests.test_camera_action_export tests.test_camera_action_model +``` + +The helper always selects the first registered training demonstration. It writes progress after each measured stage, independently retained pins, exact dataset/source identities and all three hit times. It cannot fit models or execute native simulation. An unavailable optional host metadata query is recorded without discarding measurements. diff --git a/docs/camera-action-v02-preflight.md b/docs/camera-action-v02-preflight.md new file mode 100644 index 0000000..8436347 --- /dev/null +++ b/docs/camera-action-v02-preflight.md @@ -0,0 +1,147 @@ +# Camera-to-action v0.2: reference-limiter preflight + +**9 November 2026 — the numerical reference-equivalence gate passes.** This +checks one prerequisite for the proposed Cabs/CΔ action-representation contrast. +It does not train a policy, improve the v0.1 result, or qualify an installable +skill. The frozen v0.1 source and evidence were not changed. + +The [executable check](../benchmarks/camera-action-v02-preflight/preflight.py) +compares the original 20 reference updates against issuing their projected +endpoint. It executes only the two NumPy update statements extracted from the +hash-pinned `PiperTaskEnv.step`; no simulator, renderer, policy, teacher or +recording is loaded. The pinned upstream PiPER XML is parsed to check joint +ranges, actuator order and the inherited reference ranges. The XML is not +compiled into a physical model in this check. + +## What was frozen and measured + +The original defaults remain 1 ms per update, 20 updates per decision, +1.5 rad/s arm-reference slew and 0.05 m/s single-finger jaw-reference slew. +Thus a 20 ms interval allows at most 0.03 rad per arm reference and 0.001 m in the +jaw reference. These are command-reference limits, not guarantees of actual +joint speed, jaw separation, contact force or stopping distance. + +Before comparison, the script wrote the complete case list and protocol: + +- 146 explicit hold, native-boundary, mixed-direction, within-one-tick, + exact-tick, interval-edge and one-ULP-from-boundary cases; +- 2,048 independent uniform bounded reference/target pairs; +- 2,048 bounded pairs near the 20 ms slew allowance; +- a fixed NumPy PCG64 seed of 171709; +- a fixed absolute tolerance of 1e-12 in each native coordinate, with zero + relative tolerance. + +These are synthetic numerical vectors reserved for development checks. They +are **not** collected robot episodes, extra training examples, or confirmation +scenes. No v0.1 training, development or confirmation recording was read. + +| Comparison | Cases within the frozen tolerance | Bitwise-identical cases | Largest arm error | Largest jaw error | +| --- | ---: | ---: | ---: | ---: | +| Closed-form endpoint issued through original updates | 4,242/4,242 | 883/4,242 | 1.33e-15 rad | 2.78e-17 m | +| Original 20-update endpoint issued again | 4,242/4,242 | 4,242/4,242 | 0 | 0 | +| CΔ numerical encode/decode, then original updates | 4,242/4,242 | 883/4,242 | 1.33e-15 rad | 2.78e-17 m | + +Each comparison checks all **593,880 reference entries**, not only the final +endpoint. Closed-form projection and repeated floating-point addition are not +bitwise equivalent in general. The pass is explicitly numerical equivalence +under the predeclared tolerance; a consumer requiring exact byte reproduction +must preserve the original sequence of 20 updates and its dtype/operation order. + +All 24 negative contract/input cases were rejected on both preflight paths. +They include changed rates, timestep, interval, microstep count, joint/jaw +limits, reordered joints, nonfinite or nonnumeric values, out-of-bound references, +and measured/future/teacher-target state substituted for a previous applied +reference. These are **preflight input guards**, not claims that the native +simulator implements a telemetry provenance check. + +Twenty unit tests passed, including changed source/XML rejection, preservation +of an existing output directory, and a deliberately reordered microstep history +that reaches the same endpoint but must fail equivalence. Source-parser mistakes +found while developing the check were fixed before the frozen numerical run; +the retained development test log is separate from the final passing log. + +The measured comparison section took 3.370 seconds with Python 3.12.9, +NumPy 2.5.3 and ARM64 macOS 26.5.2. This single local wall clock includes +comparisons, negative checks and measurement-file writing; it excludes initial +source/XML validation, vector generation, protocol/case writes and final report +writing. It is not a robot inference, training or dedicated hardware speed +benchmark. No CPU model, energy use or monetary compute cost was measured here. + +## Why the endpoints agree + +For each coordinate, let `r` be the preceding **applied servo reference**, `a` +the fixed teacher target, `d` the unchanged per-tick reference allowance, and +`N = 20`. Exact-real arithmetic gives the original reference sequence + +```text +r[k] = r + sign(a-r) * min(abs(a-r), k*d), k = 1..20 +P = r + clip(a-r, -20*d, +20*d) +``` + +If `a` is reached inside the interval, `P = a`. Otherwise `P` is exactly the +last allowed reference in the original direction. For every `k ≤ 20`, issuing +`P` therefore traverses the same reference sequence. Because `r` and `a` are +both within each original coordinate bound, this monotone sequence also stays +within it. The numerical check measures the small departures introduced by +float64 subtraction, repeated addition and CΔ encode/decode. + +This argument depends on a constant target, constant independent slew limits, +the preceding applied reference and an unchanged update interval. It does not +cover a measured-joint-relative target, an actuator-opening pulse, variable +rates, acceleration limiting, force control or coupled physical dynamics. +A typed `previous_applied_servo_reference` field can reject a declared wrong +state type; it cannot prove that a dishonest producer supplied authentic +telemetry. Future episode integration must bind that reference to the preceding +sealed actuator command exactly as the v0.1 export does. + +## Decision and next bounded screen + +The reference-projection prerequisite in the existing +[v0.2 proposal](camera-action-v02-proposal.md) can proceed to implementation of a +**separately versioned** Cabs/CΔ model/export contract. The remaining prerequisites +are still outstanding: matching initial decoded model heads, identical feasible +endpoint labels and loss units, training-only normalization, exact preceding +reference bindings, and fresh predeclared evaluation groups. + +Keep the proposed contrasts separate: learner-state coverage versus B0, +physical-scale absolute targets versus B0, and CΔ versus Cabs. Do not combine +favorable choices or tune against v0.1 confirmation. The proposal's 164-attempt +screen remains **unrun** and requires storage/resource preflight and registration +before collection. It awards no qualified-skill label by itself. Fewer clipped +commands, smaller prediction loss or fewer contacts without task completion +would not establish progress toward an acquired skill. + +## Evidence and reproduction + +[Full protocol](../benchmarks/camera-action-v02-preflight/evidence-20261109/protocol.json), +[all numeric vectors](../benchmarks/camera-action-v02-preflight/evidence-20261109/cases.json), +[every comparison](../benchmarks/camera-action-v02-preflight/evidence-20261109/measurements.json), +[report](../benchmarks/camera-action-v02-preflight/evidence-20261109/report.json), +and [passing test log](../benchmarks/camera-action-v02-preflight/tests-20261109.log) +are retained. The source base is +`ab9082e1ee2b2cc91c7c5fd3f1358727b3789c66`; six source-file hashes and the upstream +PiPER XML hash are included in the protocol. No credentials, model weights or +human media are part of this evidence. + +| Artifact | SHA-256 | +| --- | --- | +| Protocol | `55a32578740170841a26bf3c06a36778c8c5e56595cd5003967a2c67dd3fffc1` | +| Cases | `5ffc870ddb0b6e7b7187a41558b17b3b47c9a3df479cdd4df949bc814648f766` | +| Measurements | `3b0f235bdee6f5ef3add2e793fcb4d625f926eb28de1fb6f348dc79df2ad345c` | +| Report | `b27b758bd591196aa7f37c788fe12ca70548eab2d3adf1d830f1601ff8eeb87f` | + +Use a fresh output path. The only extra input is the existing separately pinned +PiPER XML; no mesh or native renderer is needed: + +```sh +python benchmarks/camera-action-v02-preflight/preflight.py \ + --piper-xml /path/to/verified/assets/agilex_piper/piper.xml \ + --output /path/to/new/numerical-evidence + +DVIDIA_PREFLIGHT_PIPER_XML=/path/to/verified/assets/agilex_piper/piper.xml \ + python -B -m unittest discover \ + -s benchmarks/camera-action-v02-preflight -p test_preflight.py -v +``` + +The script binds to the exact original six source files. A changed source or XML +fails closed rather than silently becoming a different numerical experiment. diff --git a/docs/camera-action-v02-proposal.md b/docs/camera-action-v02-proposal.md index 565947c..fe7321c 100644 --- a/docs/camera-action-v02-proposal.md +++ b/docs/camera-action-v02-proposal.md @@ -1,5 +1,40 @@ # Camera-to-action v0.2: proposed control-learning ablations +## Status addendum — 9 November 2026 + +The original 1 November proposal is preserved below as a dated record. Its +statements that v0.1 results were pending and no v0.2 work had run describe that +original evidence cutoff, not the present state. + +The completed v0.1 study reports **5/64 strict learned placements**, versus +9/64 matched blind, 31/64 fixed primitive and 64/64 authored teacher. The model +remains an unqualified research candidate. The resumed independent audit passed +with zero errors across all 452 scheduled attempts, 452 numeric outcome +reconstructions and 2,384,532 verified files; it executed no physics, estimator +or model. The audit receipt is `full-study-audit-resumed-20261109.json`, SHA-256 +`2774959f8e1a5be7283cea129da0ffea000d8375eb445140c8c7a60ab15efed8`. +This byte/clock/authority/outcome audit is not source authentication or hardware +qualification. The interrupted earlier audit output is preserved separately. + +Two additive pieces of groundwork now exist: + +- The [numerical limiter preflight](camera-action-v02-preflight.md) passes the + Cabs/CΔ reference-equivalence prerequisite on 4,242 bounded numerical cases + under a predeclared 1e-12 native-unit tolerance. Closed-form float64 projection + is not universally bitwise identical. No model was trained or evaluated. +- The [verified export cache](camera-action-export-cache-v01.md) reduces repeated + preparation cost on one measured training episode while preserving numeric + features, targets and dataset identity. Hits verify derived cached bytes, not + raw recordings; this is not a control-performance gain. + +The five-candidate, **164-attempt learning screen below remains unrun**. Its +proposal has not been converted into a registration or qualification result. +Matching model-head initialization, training-only normalization and fresh group +registration remain required. Neither new tool changes the frozen v0.1 sources, +models, scenes, confirmation results or gates. + +## Original proposal — 1 November 2026 + **Proposal only, 2026-11-01. Nothing below is implemented, run, or registered.** The v0.1 correction and confirmation results are pending at this proposal's evidence cutoff. Finish, audit and report that study unchanged. This document diff --git a/pyproject.toml b/pyproject.toml index 6c7574f..39e625e 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta" [project] name = "dvidia-training" -version = "0.1.3.dev4" +version = "0.1.3.dev5" description = "Local CPU training from Skillspace footage, with optional simulation movement candidates" readme = "README.md" license = "MIT AND Apache-2.0" diff --git a/src/dvidia_training/camera_action_cache.py b/src/dvidia_training/camera_action_cache.py new file mode 100644 index 0000000..9c99bb4 --- /dev/null +++ b/src/dvidia_training/camera_action_cache.py @@ -0,0 +1,382 @@ +"""Explicit, content-bound cache for verified camera-action learning exports. + +Build calls the unchanged strict exporter. A cache hit validates cached bytes, +not the raw recordings: keep the returned pins outside the cache in a trusted run +record. This optional module does not change v0.1 study orchestration or fitting. +""" +from __future__ import annotations + +import argparse +from hashlib import sha256 +import io +import json +import os +from pathlib import Path +import shutil +import stat +import tempfile + +import numpy as np + +from . import camera_action_export as export +from . import camera_action_model as model +from . import camera_action_study as study + +SCHEMA = 'dvidia.camera-action-export-cache/v1' +MAX_SAMPLES = 128_000 +RESERVE_BYTES = 30 * 1024**3 +FILES = {'manifest.json', 'features.npy', 'targets.npy'} +SCOPE = ('Cached derived learning arrays, not raw recording revalidation, source authentication, ' + 'training, native simulation or hardware qualification.') + + +def _digest(value): + return sha256(model.canonical(value)).hexdigest() + + +def _hash(value, name): + return model._hash(value, name) + + +def _path(value): + path = Path(os.path.abspath(value)) + if any(p.is_symlink() for p in (path, *path.parents)): + raise ValueError('Cache and source paths must not traverse symlinks; use canonical /private/tmp on macOS.') + return path + + +def _bytes(path, maximum): + path = _path(path) + fd = os.open(path, os.O_RDONLY | getattr(os, 'O_NOFOLLOW', 0)) + try: + before = os.fstat(fd) + if not stat.S_ISREG(before.st_mode) or before.st_nlink != 1 or not 0 < before.st_size <= maximum: + raise ValueError('Expected one bounded ordinary file without hard links.') + with os.fdopen(fd, 'rb', closefd=False) as stream: + body = stream.read(maximum + 1) + after = os.fstat(fd) + if len(body) != before.st_size or (before.st_dev, before.st_ino, before.st_size, before.st_mtime_ns, before.st_ctime_ns) != (after.st_dev, after.st_ino, after.st_size, after.st_mtime_ns, after.st_ctime_ns): + raise ValueError('File changed while being read.') + return body + finally: + os.close(fd) + + +def _json(path, maximum=16 * 1024**2): + body = _bytes(path, maximum) + return model.core._decode(body), sha256(body).hexdigest() + + +def source_identity(): + """Exact implementation identity, including all existing registered sources.""" + return dict(runtime=study.runtime_hashes(), feature_contract_sha256=model.FEATURE_CONTRACT_SHA256, + cache_source_sha256=sha256(Path(__file__).read_bytes()).hexdigest()) + + +def source_digest(): + return _digest(source_identity()) + + +def _reserve(parent, extra): + if shutil.disk_usage(parent).free < RESERVE_BYTES + extra: + raise ValueError('Cache refused: preserve at least 30 GiB free disk after the bounded write.') + + +def _write(path, body): + # A fresh cache directory has no usable identity until manifest.json is + # atomically linked last. Interrupted directories stay visibly unsealed. + temporary = None + try: + with tempfile.NamedTemporaryFile(dir=path.parent, prefix='.pending-', delete=False) as stream: + temporary = Path(stream.name) + stream.write(body); stream.flush(); os.fsync(stream.fileno()) + os.link(temporary, path) + finally: + if temporary is not None: + temporary.unlink(missing_ok=True) + # Windows refuses unlinking a read-only hard link. Remove the writable + # temporary name first, then seal the complete, atomically linked target. + path.chmod(0o444) + + +def _selection(root, expected_protocol_sha256, split, stage, attempt_ids): + if split not in ('train', 'development'): + raise ValueError('Only train or development exports are eligible; confirmation is never learning data.') + if stage not in ('demonstrations', 'corrections') or (stage == 'corrections' and split != 'train'): + raise ValueError('Corrections are training-only; choose demonstrations or corrections.') + protocol, protocol_sha = _json(root / 'protocol.json') + if protocol_sha != _hash(expected_protocol_sha256, 'expected protocol'): + raise ValueError('Protocol differs from caller expectation.') + registration, registration_sha = _json(root / 'registration.json') + runtime = study.runtime_hashes() + if (protocol.get('schema') != study.SCHEMA or registration.get('schema') != study.SCHEMA + '/registration' + or registration.get('protocol_sha256') != protocol_sha + or registration.get('source_sha256') != protocol.get('source_sha256') + or runtime != protocol.get('source_sha256')): + raise ValueError('Registered source or protocol identity is inconsistent with this exporter.') + # The registered roster owns group assignments; do not trust an episode's + # claimed split or a caller-supplied path as an admission rule. + ownership = {} + cases = {} + for part in ('train', 'development', 'confirmation'): + for case in protocol['cases'][part]: + if case['split'] != part or (case['group_id'] in ownership and ownership[case['group_id']] != part): + raise ValueError('Starting-position groups cross registered splits.') + if case['id'] in cases: + raise ValueError('Duplicate registered case identity.') + ownership[case['group_id']] = part; cases[case['id']] = case + receipt, receipt_sha = _json(root / 'stages' / (stage + '.json')) + seal, seal_sha = _json(root / 'stages' / (stage + '.integrity.json')) + if (seal != dict(sha256=receipt_sha, protocol_sha256=protocol_sha) + or receipt.get('schema') != study.SCHEMA + '/stage' or receipt.get('stage') != stage + or receipt.get('protocol_sha256') != protocol_sha or receipt.get('status') != 'complete'): + raise ValueError('A complete sealed stage with the expected protocol is required.') + roster = protocol['rosters'][stage] + rows = receipt['rows'] + if receipt['scheduled'] != len(roster) or [r['id'] for r in rows] != [r['id'] for r in roster]: + raise ValueError('Stage rows must exactly match the ordered registered roster.') + selected = [] + for row, entry in zip(rows, roster): + if any(row.get(k) != entry.get(k) for k in ('id', 'case', 'controller', 'negative_control')): + raise ValueError('Stage case, controller or negative-control binding changed.') + case = row['case'] + if cases.get(case['id']) != case or row['path'] != f'episodes/{stage}/{row["id"]}': + raise ValueError('Unregistered case or episode path.') + eligible = (case['split'] == split and row.get('complete') is True + and row.get('initial_anchor_available') is True and row.get('initial_anchor_binding_valid') is True + and (stage == 'corrections' or row.get('strict_success') is True)) + if eligible: + selected.append(row) + if attempt_ids is not None: + if (type(attempt_ids) not in (list, tuple) or not attempt_ids or len(set(attempt_ids)) != len(attempt_ids) + or any(type(x) is not str for x in attempt_ids)): + raise ValueError('Provide unique ordered eligible attempt IDs.') + requested = set(attempt_ids) + selected = [row for row in selected if row['id'] in requested] + if [row['id'] for row in selected] != list(attempt_ids): + raise ValueError('Requested attempts are ineligible, in the wrong split or out of protocol order.') + if not selected: + raise ValueError('No eligible learning episodes in the selected split.') + counts = [r['recorded_complete_intervals'] for r in selected] + if any(type(n) is not int or not 1 <= n <= 1000 for n in counts) or sum(counts) > MAX_SAMPLES: + raise ValueError('Episode or cache sample budget exceeded.') + binding = dict(protocol_sha256=protocol_sha, registration_sha256=registration_sha, + stage=stage, stage_sha256=receipt_sha, stage_seal_sha256=seal_sha, split=split) + return selected, binding + + +def _validate_features(x, counts, blind): + if not np.isfinite(x).all() or np.any(np.abs(x) > 10.000001): + raise ValueError('Features must be bounded and finite.') + names = model.FEATURE_NAMES + for i, name in enumerate(names): + if name.endswith('_available') or name.endswith(':history_present'): + if not np.isin(x[:, i], (0., 1.)).all(): + raise ValueError('Availability and history masks must be binary.') + if '_age_s/' in name and (np.any(x[:, i] < 0.) or np.any(x[:, i] > 1.000001)): + raise ValueError('Normalized sensor/history age is outside the causal contract.') + offset = 0 + for count in counts: + segment = x[offset:offset + count]; offset += count + if not np.allclose(segment[:, 8], np.arange(count, dtype=np.float64) * .001, rtol=0., atol=6e-8): + raise ValueError('Episode rows must retain increasing causal 20 ms order.') + if np.any(segment[:, :8] != segment[0, :8]) or np.any(segment[:, 3] != 0.): + raise ValueError('Historical visual anchor and fixed destination must be constant per episode.') + for lag in model.LAGS: + prefix = f'lag{round(lag * 1000)}:' + command_start = names.index(prefix + model.COMMAND_NAMES[0]) + present = x[:, names.index(prefix + 'history_present')] # command history + if np.any(x[present == 0., command_start:command_start + len(model.COMMAND_NAMES)] != 0.): + raise ValueError('Absent command-history slots must remain zero.') + if blind: + continue + start = model.LIVE_FEATURE_START + list(model.LAGS).index(lag) * len(model.SENSOR_NAMES) + live_present = x[:, start + len(model.SENSOR_NAMES) - 2] + if not np.array_equal(present, live_present): + raise ValueError('Command and live history availability must match.') + if np.any(x[live_present == 0., start:start + len(model.SENSOR_NAMES)] != 0.): + raise ValueError('Absent live-history slots must remain zero.') + for field, size, _ in model.SENSOR_SPECS: + mask_index = names.index(prefix + field + '_available') + if np.any(x[x[:, mask_index] == 0., mask_index-size:mask_index] != 0.): + raise ValueError('Unavailable sensor values must stay zero.') + mask_index = names.index(prefix + 'visual_available') + if np.any(x[x[:, mask_index] == 0., mask_index-4:mask_index] != 0.): + raise ValueError('Unavailable visual position and uncertainty must stay zero.') + if blind and np.any(x[:, model.LIVE_FEATURE_START:] != 0.): + raise ValueError('Blind exports must mask every live feedback feature.') + + +def build_cache(study_root, output, *, expected_protocol_sha256, split='train', + stage='demonstrations', attempt_ids=None, blind=False): + """Strictly export selected sealed episodes, then seal a fresh local cache. + + The returned pins must be retained outside this cache before subsequent hits. + Raw data is verified now only. Run with exclusive access to immutable inputs; + this is content integrity, not an authenticated producer attestation. + """ + if type(blind) is not bool: + raise ValueError('blind must be boolean.') + root, out = _path(study_root), _path(output) + if out == root or root in out.parents: + raise ValueError('Cache output must be outside the immutable study.') + if out.exists() or not out.parent.is_dir(): + raise ValueError('Use a fresh cache directory in an existing parent.') + if (root / 'worker.lock').exists(): + raise ValueError('Do not cache an actively written study.') + rows, binding = _selection(root, expected_protocol_sha256, split, stage, attempt_ids) + _reserve(out.parent, sum(r['recorded_complete_intervals'] for r in rows) * (model.FEATURE_COUNT*4 + 7*8) + 2*1024**2) + identity = source_identity() + label = 'issued' if stage == 'demonstrations' else 'teacher_query' + datasets, episode_bindings = [], [] + for row in rows: + directory = _path(root / row['path']) + metadata = {name: sha256(_bytes(directory/name, 128*1024**2)).hexdigest() + for name in ('recording.json', 'integrity.json', 'rollout.json')} + if metadata['integrity.json'] != row['integrity_sha256'] or metadata['rollout.json'] != row['receipt_sha256']: + raise ValueError('Episode integrity or receipt differs from sealed stage.') + dataset = export.export_episode(directory, blind=blind, label_source=label) + source = dataset['provenance']['episodes'][0] + if (source['recording_sha256'] != metadata['recording.json'] or source['integrity_sha256'] != metadata['integrity.json'] + or source['sample_count'] != row['recorded_complete_intervals'] + or source['case_id'] != row['case']['id'] or source['source_group'] != row['case']['group_id']): + raise ValueError('Strict export provenance differs from the registered episode.') + if any(sha256(_bytes(directory/name, 128*1024**2)).hexdigest() != value for name, value in metadata.items()): + raise ValueError('Source episode changed during strict export.') + datasets.append(dataset) + episode_bindings.append(dict(attempt_id=row['id'], path=row['path'], case=row['case'], + label_source=label, metadata_sha256=metadata)) + after_rows, after_binding = _selection(root, expected_protocol_sha256, split, stage, attempt_ids) + if after_binding != binding or after_rows != rows or source_identity() != identity: + raise ValueError('Stage or implementation changed during strict export.') + # Single-episode identity is preserved exactly; multi-episode identity uses + # the original combiner and its explicit label provenance unchanged. + dataset = datasets[0] if len(datasets) == 1 else export.combine_datasets(datasets) + x = np.asarray(dataset['features'], dtype=' 1 and sys.argv[1] == 'cache': + from .camera_action_cache import main as cache_main + raise SystemExit(cache_main(sys.argv[2:])) if len(sys.argv) > 1 and sys.argv[1] == 'robot': from .camera_action_study import main as robot_main raise SystemExit(robot_main(sys.argv[2:])) parser = argparse.ArgumentParser(description=__doc__) commands = parser.add_subparsers(dest='command', required=True) + commands.add_parser('cache', help='Build or verify pinned paired-demonstration caches for repeated local learning.') for name in ('prepare', 'run'): action = commands.add_parser(name) action.add_argument('source', help='Skillspace folder, ZIP, manifest, prepared dataset or public DVIDIA URL.') diff --git a/tests/test_camera_action_cache.py b/tests/test_camera_action_cache.py new file mode 100644 index 0000000..41cf115 --- /dev/null +++ b/tests/test_camera_action_cache.py @@ -0,0 +1,272 @@ +from hashlib import sha256 +import io +import json +from pathlib import Path +import shutil +import stat +import tempfile +import unittest +from unittest.mock import patch + +import numpy as np + +from dvidia_training import camera_action_cache as cache +from dvidia_training import camera_action_export as export +from dvidia_training import camera_action_model as model +from dvidia_training import camera_action_study as study +from tests.test_camera_action_export import fixture + + +def write(path, value): + path.parent.mkdir(parents=True, exist_ok=True) + path.write_bytes(model.canonical(value) + b'\n') + return sha256(path.read_bytes()).hexdigest() + + +class CacheTests(unittest.TestCase): + def setUp(self): + # CI fixture tests must not require 30 GiB of actual host free space. + # The explicit low-disk test applies its narrower nested patch below. + ample = shutil._ntuple_diskusage(200 * 1024**3, 50 * 1024**3, 150 * 1024**3) + disk_usage = patch.object(cache.shutil, 'disk_usage', return_value=ample) + disk_usage.start() + self.addCleanup(disk_usage.stop) + self.temp = tempfile.TemporaryDirectory() + self.root = Path(self.temp.name).resolve() + self.study = self.root/'study'; self.study.mkdir() + self.out = self.root/'cache' + self.recordings = {} + self.rows, cases = [], {'train': [], 'development': [], 'confirmation': []} + for group, split in [('train-a', 'train'), ('train-b', 'train'), ('dev-a', 'development')]: + case = dict(id=group+'-goal0', group_id=group, split=split, goal_id=0, + goal_position_m=[.35, .08, .08], object_position_m=[.3, -.03, .082], seed=17) + cases[split].append(case) + attempt = case['id']+'-teacher'; relative = 'episodes/demonstrations/'+attempt + episode = self.study/relative; episode.parent.mkdir(parents=True, exist_ok=True) + recording = fixture(episode, group=group) + self.recordings[str(episode)] = recording + receipt = write(episode/'rollout.json', {'status': 'complete'}) + self.rows.append(dict(id=attempt, case=case, controller='teacher', negative_control=None, + path=relative, complete=True, initial_anchor_available=True, initial_anchor_binding_valid=True, + strict_success=True, recorded_complete_intervals=3, receipt_sha256=receipt, + integrity_sha256=sha256((episode/'integrity.json').read_bytes()).hexdigest())) + self.protocol = dict(schema=study.SCHEMA, source_sha256=study.runtime_hashes(), cases=cases, + rosters={'demonstrations': [{k: r[k] for k in ('id','case','controller','negative_control')} for r in self.rows]}) + self.save_protocol() + self.save_stage() + self.capture = patch('dvidia_training.camera_action_capture.load_rollout', side_effect=lambda p: self.recordings[str(p)]) + self.capture.start() + + def tearDown(self): + self.capture.stop() + for path in self.root.rglob('*'): + if not path.is_symlink(): + path.chmod(0o755 if path.is_dir() else 0o644) + self.temp.cleanup() + + def save_protocol(self): + self.protocol_sha = write(self.study/'protocol.json', self.protocol) + write(self.study/'registration.json', dict(schema=study.SCHEMA+'/registration', + source_sha256=self.protocol['source_sha256'], protocol_sha256=self.protocol_sha)) + + def save_stage(self): + h = write(self.study/'stages/demonstrations.json', dict(schema=study.SCHEMA+'/stage', stage='demonstrations', + protocol_sha256=self.protocol_sha, status='complete', scheduled=len(self.rows), rows=self.rows)) + write(self.study/'stages/demonstrations.integrity.json', dict(sha256=h, protocol_sha256=self.protocol_sha)) + + def build(self, **kw): + self.pins = cache.build_cache(self.study, self.out, expected_protocol_sha256=self.protocol_sha, **kw) + return self.pins + + def load(self, **kw): + args = dict(expected_manifest_sha256=self.pins['manifest_sha256'], expected_protocol_sha256=self.protocol_sha, + expected_split=self.pins['split'], expected_source_sha256=self.pins['source_sha256']) + args.update(kw) + return cache.load_cache(self.out, **args) + + def amend(self, *, transform=None, manifest_change=None): + self.out.chmod(0o755) + manifest = json.loads((self.out/'manifest.json').read_text()) + if transform: + p = self.out/'features.npy'; value = np.load(p, allow_pickle=False); value = transform(value) + stream = io.BytesIO(); np.save(stream, value, allow_pickle=False) + p.chmod(0o644); p.write_bytes(stream.getvalue()) + manifest['arrays']['features.npy']['sha256'] = sha256(p.read_bytes()).hexdigest() + manifest['arrays']['features.npy']['bytes'] = p.stat().st_size + if manifest_change: + manifest_change(manifest) + (self.out/'manifest.json').chmod(0o644) + return write(self.out/'manifest.json', manifest) + + def test_atomic_write_removes_writable_temporary_before_sealing_target(self): + target = self.root/'portable-write.bin' + unlinked = [] + original_unlink = Path.unlink + def writable_unlink(path, *args, **kwargs): + if path.name.startswith('.pending-'): + self.assertTrue(path.stat().st_mode & stat.S_IWUSR) + unlinked.append(path.name) + return original_unlink(path, *args, **kwargs) + with patch.object(Path, 'unlink', writable_unlink): + cache._write(target, b'complete cached artifact') + self.assertEqual(len(unlinked), 1) + self.assertEqual(target.read_bytes(), b'complete cached artifact') + self.assertFalse(target.stat().st_mode & stat.S_IWUSR) + self.assertEqual(list(self.root.glob('.pending-*')), []) + # An existing target is never replaced, and its failed writer leaves + # no temporary file behind on either POSIX or Windows semantics. + with self.assertRaises(FileExistsError): + cache._write(target, b'replacement must not happen') + self.assertEqual(target.read_bytes(), b'complete cached artifact') + self.assertEqual(list(self.root.glob('.pending-*')), []) + + def test_equality_to_strict_export_and_no_raw_reads_on_hit(self): + strict = export.combine_datasets([export.export_episode(self.study/r['path']) for r in self.rows[:2]]) + self.build() + with patch.object(export, 'export_episode', side_effect=AssertionError('must not export on hit')): + loaded = self.load() + np.testing.assert_array_equal(strict['features'], loaded['features']) + np.testing.assert_array_equal(strict['targets'], loaded['targets']) + self.assertEqual(strict['provenance'], loaded['provenance']) + self.assertEqual(strict['features'].dtype, np.dtype('float64')) + self.assertEqual(loaded['features'].dtype, np.dtype('float32')) + self.assertEqual(model._dataset(strict, blind=False)[-1], self.pins['dataset_sha256']) + self.assertFalse(loaded['features'].flags.writeable) + # Cache remains a snapshot of validated source bytes even if raw data is + # later removed; this explicitly does NOT reverify raw bytes on a hit. + shutil.rmtree(self.study) + np.testing.assert_array_equal(loaded['features'], self.load()['features']) + + def test_single_episode_blind_is_identical(self): + first = self.rows[0] + strict = export.export_episode(self.study/first['path'], blind=True) + self.build(attempt_ids=[first['id']], blind=True) + loaded = self.load() + np.testing.assert_array_equal(strict['features'], loaded['features']) + self.assertEqual(strict['provenance'], loaded['provenance']) + self.assertTrue(np.all(loaded['features'][:, model.LIVE_FEATURE_START:] == 0.)) + + def test_missing_masks_retained(self): + self.build(attempt_ids=[self.rows[0]['id']]) + x = self.load()['features']; i = model.FEATURE_NAMES.index('lag0:visual_available') + self.assertEqual(x[:, i].tolist(), [1., 0., 1.]) + self.assertTrue(np.all(x[1, i-4:i] == 0.)) + + def test_expected_pins_are_required_and_self_edited_manifest_is_not_authority(self): + self.build() + for kw in [dict(expected_manifest_sha256='0'*64), dict(expected_protocol_sha256='0'*64), + dict(expected_source_sha256='0'*64), dict(expected_split='development')]: + with self.subTest(kw=kw), self.assertRaises(ValueError): + self.load(**kw) + self.amend(manifest_change=lambda m: m.update(dataset_sha256='0'*64)) + with self.assertRaisesRegex(ValueError, 'independently retained'): + self.load() + + def test_unknown_files_and_unsealed_directories_fail(self): + self.build() + self.out.chmod(0o755) + (self.out/'extra').write_text('not allowed') + with self.assertRaises(ValueError): self.load() + (self.out/'extra').unlink() + (self.out/'manifest.json').chmod(0o644) + (self.out/'manifest.json').unlink() + with self.assertRaises(ValueError): self.load() + + def test_symlinked_cache_file_fails_when_platform_permits_fixture(self): + self.build() + self.out.chmod(0o755) + original = self.out/'features.npy'; moved = self.root/'moved.npy'; original.rename(moved) + try: + original.symlink_to(moved) + except (OSError, NotImplementedError): + moved.rename(original) + self.skipTest('This host does not permit symlink creation') + with self.assertRaisesRegex(ValueError, 'symlink'): self.load() + + def test_hardlinked_cache_file_fails_when_platform_permits_fixture(self): + self.build() + self.out.chmod(0o755) + original = self.out/'features.npy'; moved = self.root/'moved.npy'; original.rename(moved) + try: + original.hardlink_to(moved) + except (OSError, NotImplementedError): + moved.rename(original) + self.skipTest('This host does not permit hard-link creation') + with self.assertRaisesRegex(ValueError, 'ordinary'): self.load() + + def test_changed_reordered_truncated_arrays_fail(self): + self.build() + p = self.out/'features.npy'; p.chmod(0o644); original = p.read_bytes() + for body in (original[:-1], original[:140]+bytes([original[140]^1])+original[141:]): + p.write_bytes(body) + with self.assertRaises(ValueError): self.load() + p.write_bytes(original) + x = np.load(p, allow_pickle=False); np.save(p, x[::-1], allow_pickle=False) + with self.assertRaisesRegex(ValueError, 'array bytes'): self.load() + + def test_rebound_bad_masks_nan_order_and_dtype_still_fail(self): + self.build(attempt_ids=[self.rows[0]['id']]) + manifest_body=(self.out/'manifest.json').read_bytes(); array_body=(self.out/'features.npy').read_bytes() + def mask(x): + x[1, model.FEATURE_NAMES.index('lag0:visual_available')] = .5; return x + def filled_missing(x): + x[1, model.FEATURE_NAMES.index('lag0:visual_x_m/.5')] = 1.; return x + def nan(x): x[1, 0]=float('nan'); return x + for transform in (mask, filled_missing, nan, lambda x: x[::-1], lambda x: x.astype(np.float64)): + self.out.chmod(0o755) + for name, body in [('manifest.json',manifest_body),('features.npy',array_body)]: + p=self.out/name;p.chmod(0o644);p.write_bytes(body) + amended = self.amend(transform=transform) + with self.subTest(transform=transform), self.assertRaises(ValueError): + self.load(expected_manifest_sha256=amended) + + def test_split_and_protocol_order_prevent_leakage(self): + for kw in (dict(split='confirmation'), dict(attempt_ids=[self.rows[2]['id']]), + dict(attempt_ids=[self.rows[1]['id'], self.rows[0]['id']]), + dict(attempt_ids=[self.rows[0]['id'], self.rows[0]['id']]), + dict(stage='corrections', split='development')): + with self.subTest(kw=kw), self.assertRaises(ValueError): self.build(**kw) + self.protocol['cases']['development'][0]['group_id'] = 'train-a' + self.save_protocol(); self.save_stage() + with self.assertRaisesRegex(ValueError, 'cross registered splits'): self.build() + + def test_source_and_episode_seals_are_checked_before_build(self): + episode=self.study/self.rows[0]['path']; (episode/'integrity.json').write_text('changed') + with self.assertRaisesRegex(ValueError, 'sealed stage'): self.build() + self.assertFalse(self.out.exists()) + + def test_correction_uses_teacher_queries_and_preserves_executed_authority(self): + row = dict(self.rows[0]); row['controller'] = 'mixed'; row['id'] = 'correction-' + row['case']['id'] + '-mixed' + row['path'] = 'episodes/corrections/' + row['id']; row['strict_success'] = False + episode = self.study / row['path']; episode.parent.mkdir(parents=True) + self.recordings[str(episode)] = fixture(episode, mode='mixed', group=row['case']['group_id']) + row['receipt_sha256'] = write(episode/'rollout.json', {'status':'complete'}) + row['integrity_sha256'] = sha256((episode/'integrity.json').read_bytes()).hexdigest() + self.protocol['rosters']['corrections'] = [{k: row[k] for k in ('id','case','controller','negative_control')}] + self.save_protocol() + h = write(self.study/'stages/corrections.json', dict(schema=study.SCHEMA+'/stage', stage='corrections', + protocol_sha256=self.protocol_sha, status='complete', scheduled=1, rows=[row])) + write(self.study/'stages/corrections.integrity.json', dict(sha256=h, protocol_sha256=self.protocol_sha)) + strict = export.export_episode(episode, label_source='teacher_query') + self.build(stage='corrections') + loaded = self.load() + np.testing.assert_array_equal(strict['targets'], loaded['targets']) + self.assertEqual(loaded['targets'][:,0].tolist(), [.8]*3) + self.assertEqual(loaded['provenance'], strict['provenance']) + self.assertEqual(self.recordings[str(episode)]['steps'][0]['command']['authority'], 'student') + + def test_active_study_low_disk_and_existing_destination_refused(self): + (self.study/'worker.lock').write_text('active') + with self.assertRaisesRegex(ValueError, 'actively'): self.build() + (self.study/'worker.lock').unlink() + with patch.object(cache.shutil, 'disk_usage', return_value=shutil._ntuple_diskusage(1,1,1)): + with self.assertRaisesRegex(ValueError, '30 GiB'): self.build() + self.assertFalse(self.out.exists()) + self.out.mkdir() + with self.assertRaisesRegex(ValueError, 'fresh'): self.build() + with self.assertRaisesRegex(ValueError, 'outside'): + cache.build_cache(self.study, self.study/'cache', expected_protocol_sha256=self.protocol_sha) + + +if __name__ == '__main__': + unittest.main() diff --git a/tests/test_camera_cache_cli.py b/tests/test_camera_cache_cli.py new file mode 100644 index 0000000..d873d45 --- /dev/null +++ b/tests/test_camera_cache_cli.py @@ -0,0 +1,45 @@ +"""Fresh-process coverage for the existing Terminal entry point.""" +import json +import os +from pathlib import Path +import subprocess +import sys +import unittest + + +class CameraCacheCliTests(unittest.TestCase): + def command(self, *arguments): + env = dict(os.environ, PYTHONPATH=str(Path(__file__).parents[1] / 'src'), + PYTHONDONTWRITEBYTECODE='1') + return subprocess.run( + [sys.executable, '-c', 'from dvidia_training.footage_pipeline import main; main()', *arguments], + env=env, capture_output=True, text=True, timeout=20) + + def test_main_help_exposes_cache_and_existing_footage_commands(self): + result = self.command('--help') + self.assertEqual(result.returncode, 0, result.stderr) + for name in ('cache', 'prepare', 'run', 'inspect'): + self.assertIn(name, result.stdout) + + def test_cache_source_can_be_pinned_from_existing_terminal_command(self): + result = self.command('cache', 'source') + self.assertEqual(result.returncode, 0, result.stderr) + value = json.loads(result.stdout) + self.assertEqual(len(value['source_sha256']), 64) + self.assertEqual(len(value['source_identity']['runtime']), 19) + + def test_cache_hit_requires_external_pins(self): + result = self.command('cache', 'load', '/private/tmp/not-a-dvidia-cache') + self.assertEqual(result.returncode, 2) + for flag in ('--manifest-sha256', '--protocol-sha256', '--split', '--source-sha256'): + self.assertIn(flag, result.stderr) + + def test_original_robot_command_keeps_its_stages(self): + result = self.command('robot', '--help') + self.assertEqual(result.returncode, 0, result.stderr) + for name in ('prepare', 'collect', 'train', 'evaluate', 'inspect', 'package'): + self.assertIn(name, result.stdout) + + +if __name__ == '__main__': + unittest.main() From 77624ca66ace1b3aa81d076fefc294fca9015711 Mon Sep 17 00:00:00 2001 From: DVIDIA Date: Mon, 9 Nov 2026 09:38:42 -0500 Subject: [PATCH 2/2] Validate cached data against all four trained dataset identities --- .../camera-action-export-cache-v01/README.md | 8 + .../full-training-results.json | 295 +++++++++++++++++ .../full-training-script-provenance.json | 20 ++ .../validate_full_training.py | 302 ++++++++++++++++++ docs/camera-action-export-cache-v01.md | 31 ++ 5 files changed, 656 insertions(+) create mode 100644 benchmarks/camera-action-export-cache-v01/full-training-results.json create mode 100644 benchmarks/camera-action-export-cache-v01/full-training-script-provenance.json create mode 100644 benchmarks/camera-action-export-cache-v01/validate_full_training.py diff --git a/benchmarks/camera-action-export-cache-v01/README.md b/benchmarks/camera-action-export-cache-v01/README.md index 0dfb3d8..fcd10d4 100644 --- a/benchmarks/camera-action-export-cache-v01/README.md +++ b/benchmarks/camera-action-export-cache-v01/README.md @@ -25,3 +25,11 @@ The focused CLI/cache/export suite passes 25 tests, including cleanup order, no- - Protocol SHA-256: `576851e321034a0f6d3cb4d0818b3a5ca97975fcc6f2c7fa30b07ffd203a2d76`. - `cli-proof.json` records fresh installed-wheel source, inspection/load, wrong-split refusal and existing CLI checks, outside the three timed loads. `cli-proof-prior-source.json` retains the earlier source-bound checks. - [Usage, trust boundary and reproduction](../../docs/camera-action-export-cache-v01.md). + +## Complete training dataset follow-up + +[full-training-results.json](full-training-results.json) covers the complete registered training split: 64 teacher and 32 mixed-control episodes, 96,000 samples, 32 start groups. Both caches were built once with strict source validation in **160.671 s**. The three verified load-and-combine measurements were **0.347 / 0.280 / 0.279 s**; the four original model-reference comparisons and blind projection took a separate **0.596 / 0.491 / 0.490 s**. All four sealed model dataset/provenance identities matched on every load (12/12 checks). + +Derived caches total 108,804,852 bytes, from a source inventory of 18,971,932,592 bytes / 577,056 files. Whole-process peak RSS was 1,631,633,408 bytes and total validation time was 163.738 s. The same shared-host caveats apply. There was no redundant strict-export baseline, no new fit, native simulation or held-out recording export, and no task-success improvement or qualification change. The repeated-load measurement does not include training. Raw recordings are verified at cache construction, not again on a hit. + +[validate_full_training.py](validate_full_training.py) is a portable version of the exact executed script, with required absolute CLI paths replacing host-specific paths. [full-training-script-provenance.json](full-training-script-provenance.json) pins both original and portable hashes; the portable variant was not run for a new measurement. All original source, protocol, stage, model and complete training-roster checks remain intact. [Reproduction and scope](../../docs/camera-action-export-cache-v01.md#complete-training-data-validation) explain the fixed dev5 environment and fresh-output requirements. This benchmark-and-documentation follow-up does not replace the released wheel or tag; the candidate remains unqualified. diff --git a/benchmarks/camera-action-export-cache-v01/full-training-results.json b/benchmarks/camera-action-export-cache-v01/full-training-results.json new file mode 100644 index 0000000..12aad8d --- /dev/null +++ b/benchmarks/camera-action-export-cache-v01/full-training-results.json @@ -0,0 +1,295 @@ +{ + "builds": [ + { + "cache_bytes": 72535147, + "pins": { + "dataset_sha256": "07b175f78e4e77cbdde9a461a4bcae4dcb0db7d389ee4f2e702ff28db8bb3dfc", + "manifest_sha256": "8acd728fcc8ed637b58138c3bd7466432a588fa439acefde4b3c90fa1adfdbaf", + "protocol_sha256": "576851e321034a0f6d3cb4d0818b3a5ca97975fcc6f2c7fa30b07ffd203a2d76", + "raw_source_reverified_on_hit": false, + "sample_count": 64000, + "source_sha256": "0ab01145c66d651eaca96d763b4bec1706327f2cdd4bd8665d05056cbdd6f677", + "split": "train" + }, + "seconds": 105.62133508402621, + "stage": "demonstrations" + }, + { + "cache_bytes": 36269705, + "pins": { + "dataset_sha256": "0561f8793ac6f68318d28c99e15ee8755c85412f3e34c990e1c4f0da4a5c1789", + "manifest_sha256": "0997805831dfaacfe38d87468587f58c4e0b3f748165816e2167c4376676b96b", + "protocol_sha256": "576851e321034a0f6d3cb4d0818b3a5ca97975fcc6f2c7fa30b07ffd203a2d76", + "raw_source_reverified_on_hit": false, + "sample_count": 32000, + "source_sha256": "0ab01145c66d651eaca96d763b4bec1706327f2cdd4bd8665d05056cbdd6f677", + "split": "train" + }, + "seconds": 55.049781042005634, + "stage": "corrections" + } + ], + "cache_module_sha256": "9191f2eb9f96bd09d4f711c31966a583bd938853a874e6018f8ddebfb0bc00d8", + "comparison_scope": "Canonical float64 numeric values, ordered groups and full provenance equal the four independently sealed model dataset identities; cache float32 storage is not original combined NPY byte identity.", + "derived_cache_bytes": 108804852, + "development_or_confirmation_recordings_read": false, + "extra_strict_exports": 0, + "fitting_runs": 0, + "hardware": { + "cpu_count": "unavailable: host metadata query refused", + "cpu_model": "unavailable: host metadata query refused", + "machine": "arm64", + "numpy": "2.5.3", + "physical_memory_bytes": "unavailable: host metadata query refused", + "platform": "macOS-26.5.2-arm64-arm-64bit", + "python": "3.12.9" + }, + "limitations": [ + "This validates offline preparation for the existing dataset; it does not change the policy or task-success result.", + "No matched strict-export baseline was run. Build and hit timings are different operations; no speedup ratio is claimed.", + "Cache-hit validation binds derived bytes, protocol, split, provenance and source implementation. Raw recordings were checked during construction, not again on each hit.", + "Validation ran on a shared host concurrently with publication work; it is not an isolated or cold-cache benchmark." + ], + "memory_scope": "Whole-process high-water RSS across metadata inspection, both builds, loads, combination and golden checks; not isolated per-stage memory.", + "model_references": { + "corrected/blind": { + "dataset_sha256": "efd1760344b88c9eb61045454968564bb45a8cd38037e2bdcdf55b343eab3903", + "model_sha256": "c3593d83b5505127a31304c8965914e01661d419dfc6c76a17a6c9bbac418806", + "provenance_sha256": "60edeb423d3810419e5ac971511c237c77e619a309637402b0974e658d7cb4a4", + "samples": 96000 + }, + "corrected/full": { + "dataset_sha256": "b500b3ba348bba44cc79e377266f92910bd7e0165c36cd8b2fe260909b30a2f9", + "model_sha256": "d176b391b61b5e331bcfe1676107c53f4c0ae6110414dfed4b07d57cbb883b0e", + "provenance_sha256": "52cbeda62e3aa50e8cd6a34688fba7583f9fcec927cb0eb434a6907c99695f4f", + "samples": 96000 + }, + "initial/blind": { + "dataset_sha256": "759fe1c0610c1768f1455ed6cdcc6305be0d463b2b1e9c48a327f4f45b9c50c7", + "model_sha256": "d30b0ae10a4fbdc34a73122a34d73fd9246ee4b87c90c2b3b1eb3a98888d707e", + "provenance_sha256": "7d5279ffd186f018a41641a18bf5d6bbf010036114abb9e902d25aadc9ca3716", + "samples": 64000 + }, + "initial/full": { + "dataset_sha256": "07b175f78e4e77cbdde9a461a4bcae4dcb0db7d389ee4f2e702ff28db8bb3dfc", + "model_sha256": "1d1f80376c89995513b518b36c4f8eca9e78efec3d3e68a10ee9988e84f4f038", + "provenance_sha256": "7103ad53111cb114cdcd164cfa15bbbf359ebc4ae66e7456ab7c1f38820b2864", + "samples": 64000 + } + }, + "native_runs": 0, + "passed": true, + "peak_process_rss_bytes": 1631633408, + "peer_review": { + "passed": true, + "scope": "Executed script/result, four pinned model dataset/provenance identities, 96-episode training roster, portable helper, public receipt normalization and documentation. This receipt changes only review state and adds this review binding after review.", + "sha256": "4190b26ace73e8d0d498e04e3223ae20c913eb93b7bc4ad49310de0dfdc39326" + }, + "policy_task_result_unchanged": true, + "protocol_sha256": "576851e321034a0f6d3cb4d0818b3a5ca97975fcc6f2c7fa30b07ffd203a2d76", + "publication_state": "locally_validated_peer_reviewed", + "qualification_changed": false, + "qualified": false, + "raw_source_reverified_on_hit": false, + "raw_training_bytes": 18971932592, + "raw_training_files": 577056, + "raw_training_inventory": { + "corrections": { + "bytes": 6333838508, + "episodes": 32, + "files": 192352, + "samples": 32000 + }, + "demonstrations": { + "bytes": 12638094084, + "episodes": 64, + "files": 384704, + "samples": 64000 + } + }, + "rounds": [ + { + "combine_seconds": 0.1124684160167817, + "golden_checks": [ + { + "dataset_sha256": "07b175f78e4e77cbdde9a461a4bcae4dcb0db7d389ee4f2e702ff28db8bb3dfc", + "episodes": 64, + "groups": 32, + "model_sha256": 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"efd1760344b88c9eb61045454968564bb45a8cd38037e2bdcdf55b343eab3903", + "episodes": 96, + "groups": 32, + "model_sha256": "c3593d83b5505127a31304c8965914e01661d419dfc6c76a17a6c9bbac418806", + "name": "corrected/blind", + "passed": true, + "provenance_sha256": "60edeb423d3810419e5ac971511c237c77e619a309637402b0974e658d7cb4a4", + "samples": 96000 + } + ], + "golden_comparison_and_blind_projection_seconds": 0.5959045839845203, + "round": 1, + "validated_cache_load_seconds": { + "corrections": 0.07494037499418482, + "demonstrations": 0.15972379202139564 + }, + "validated_load_plus_combine_seconds": 0.34713258303236216, + "whole_round_seconds": 0.9430410830245819 + }, + { + "combine_seconds": 0.09749162499792874, + "golden_checks": [ + { + "dataset_sha256": "07b175f78e4e77cbdde9a461a4bcae4dcb0db7d389ee4f2e702ff28db8bb3dfc", + "episodes": 64, + "groups": 32, + "model_sha256": "1d1f80376c89995513b518b36c4f8eca9e78efec3d3e68a10ee9988e84f4f038", + "name": "initial/full", + "passed": true, + "provenance_sha256": "7103ad53111cb114cdcd164cfa15bbbf359ebc4ae66e7456ab7c1f38820b2864", + "samples": 64000 + }, + { + "dataset_sha256": "b500b3ba348bba44cc79e377266f92910bd7e0165c36cd8b2fe260909b30a2f9", + "episodes": 96, + "groups": 32, + "model_sha256": "d176b391b61b5e331bcfe1676107c53f4c0ae6110414dfed4b07d57cbb883b0e", + "name": "corrected/full", + "passed": true, + "provenance_sha256": "52cbeda62e3aa50e8cd6a34688fba7583f9fcec927cb0eb434a6907c99695f4f", + "samples": 96000 + }, + { + "dataset_sha256": "759fe1c0610c1768f1455ed6cdcc6305be0d463b2b1e9c48a327f4f45b9c50c7", + "episodes": 64, + "groups": 32, + "model_sha256": "d30b0ae10a4fbdc34a73122a34d73fd9246ee4b87c90c2b3b1eb3a98888d707e", + "name": "initial/blind", + "passed": true, + "provenance_sha256": "7d5279ffd186f018a41641a18bf5d6bbf010036114abb9e902d25aadc9ca3716", + "samples": 64000 + }, + { + "dataset_sha256": "efd1760344b88c9eb61045454968564bb45a8cd38037e2bdcdf55b343eab3903", + "episodes": 96, + "groups": 32, + "model_sha256": "c3593d83b5505127a31304c8965914e01661d419dfc6c76a17a6c9bbac418806", + "name": "corrected/blind", + "passed": true, + "provenance_sha256": "60edeb423d3810419e5ac971511c237c77e619a309637402b0974e658d7cb4a4", + "samples": 96000 + } + ], + "golden_comparison_and_blind_projection_seconds": 0.4905752089980524, + "round": 2, + "validated_cache_load_seconds": { + "corrections": 0.060244958993280306, + "demonstrations": 0.12223020798410289 + }, + "validated_load_plus_combine_seconds": 0.27996679197531193, + "whole_round_seconds": 0.7705457909905817 + }, + { + "combine_seconds": 0.09710429201368243, + "golden_checks": [ + { + "dataset_sha256": "07b175f78e4e77cbdde9a461a4bcae4dcb0db7d389ee4f2e702ff28db8bb3dfc", + "episodes": 64, + "groups": 32, + "model_sha256": "1d1f80376c89995513b518b36c4f8eca9e78efec3d3e68a10ee9988e84f4f038", + "name": "initial/full", + "passed": true, + "provenance_sha256": "7103ad53111cb114cdcd164cfa15bbbf359ebc4ae66e7456ab7c1f38820b2864", + "samples": 64000 + }, + { + "dataset_sha256": "b500b3ba348bba44cc79e377266f92910bd7e0165c36cd8b2fe260909b30a2f9", + "episodes": 96, + "groups": 32, + "model_sha256": "d176b391b61b5e331bcfe1676107c53f4c0ae6110414dfed4b07d57cbb883b0e", + "name": "corrected/full", + "passed": true, + "provenance_sha256": "52cbeda62e3aa50e8cd6a34688fba7583f9fcec927cb0eb434a6907c99695f4f", + "samples": 96000 + }, + { + "dataset_sha256": "759fe1c0610c1768f1455ed6cdcc6305be0d463b2b1e9c48a327f4f45b9c50c7", + "episodes": 64, + "groups": 32, + "model_sha256": "d30b0ae10a4fbdc34a73122a34d73fd9246ee4b87c90c2b3b1eb3a98888d707e", + "name": "initial/blind", + "passed": true, + "provenance_sha256": "7d5279ffd186f018a41641a18bf5d6bbf010036114abb9e902d25aadc9ca3716", + "samples": 64000 + }, + { + "dataset_sha256": "efd1760344b88c9eb61045454968564bb45a8cd38037e2bdcdf55b343eab3903", + "episodes": 96, + "groups": 32, + "model_sha256": "c3593d83b5505127a31304c8965914e01661d419dfc6c76a17a6c9bbac418806", + "name": "corrected/blind", + "passed": true, + "provenance_sha256": "60edeb423d3810419e5ac971511c237c77e619a309637402b0974e658d7cb4a4", + "samples": 96000 + } + ], + "golden_comparison_and_blind_projection_seconds": 0.4896485829958692, + "round": 3, + "validated_cache_load_seconds": { + "corrections": 0.06038941699080169, + "demonstrations": 0.12157112499698997 + }, + "validated_load_plus_combine_seconds": 0.2790648340014741, + "whole_round_seconds": 0.7687164999952074 + } + ], + "schema": "dvidia.full-training-cache-publication-receipt/v1", + "source_commit": "cc6746a95669cfd69a49e32a3e6c2e5a42ce2546", + "source_read_scope": "Unique raw corpus size is metadata-bound, not measured physical I/O. Strict exporter rereads some metadata, sidecars and native trace bytes; no physics is executed.", + "source_sha256": "0ab01145c66d651eaca96d763b4bec1706327f2cdd4bd8665d05056cbdd6f677", + "stage_sha256": { + "corrections": "ae0a5653f728f147f929325c60318cb3d164c6d97d846fb96ac07ee9d27ad5cb", + "demonstrations": "5d57eac599f1686d2bdb15bb53ceebe09e899ec71dfe87039aa85de7f853c06b", + "train-corrected": "9b37a37d7b49fceb595f776d59579986f7579c7135f810b8d706199d5e4d6ddc", + "train-initial": "86be5d9c17af43c35e97677d819b1433faed54ccf930078afc0f785139acc6a9" + }, + "timing_scope": "Shared-host offline preparation. Imports excluded; builds include strict source, sidecar and saved-trace score validation. Each hit includes cache/source validation. Combiner and golden checks reported separately. No cold-cache flush, isolated CPU reservation or matched strict-export timing; no speedup claim.", + "total_validation_wall_seconds": 163.7380633749999, + "training_episodes": 96, + "training_only": true, + "training_samples": 96000, + "training_start_groups": 32, + "validation_result": { + "bytes": 16921, + "sha256": "14379c3288d16f380cade39a067f6a9315449cd7bd07f0a828243b237eff52ee" + }, + "validation_script": { + "bytes": 17276, + "sha256": "a820eb77b7d5a80dd79686f86369b29fd7a39b8bb34328e636a2de31d51318c2" + } +} diff --git a/benchmarks/camera-action-export-cache-v01/full-training-script-provenance.json b/benchmarks/camera-action-export-cache-v01/full-training-script-provenance.json new file mode 100644 index 0000000..f35f5df --- /dev/null +++ b/benchmarks/camera-action-export-cache-v01/full-training-script-provenance.json @@ -0,0 +1,20 @@ +{ + "code_source_commit": "cc6746a95669cfd69a49e32a3e6c2e5a42ce2546", + "original_executed_script": { + "bytes": 17276, + "sha256": "a820eb77b7d5a80dd79686f86369b29fd7a39b8bb34328e636a2de31d51318c2" + }, + "original_result": { + "bytes": 16921, + "sha256": "14379c3288d16f380cade39a067f6a9315449cd7bd07f0a828243b237eff52ee" + }, + "portable_script": { + "bytes": 17929, + "path": "validate_full_training.py", + "sha256": "36c31fccd0d84410d1a590b7cae7a3009700a3eec05028ccfc594cbed01037c9" + }, + "portable_variant_executed_for_measurement": false, + "schema": "dvidia.portable-benchmark-script/v1", + "scope": "Reproduction only. No new measurement or model fitting was performed for the portable helper.", + "transformation": "Added argparse with absolute-path validation and replaced the fixed study, output, expected environment and working-directory paths with required caller paths. All protocol, source, model, stage, roster, numerical checks and budgets are unchanged. The output parent replaces the original proof-directory binding." +} diff --git a/benchmarks/camera-action-export-cache-v01/validate_full_training.py b/benchmarks/camera-action-export-cache-v01/validate_full_training.py new file mode 100644 index 0000000..b0b00de --- /dev/null +++ b/benchmarks/camera-action-export-cache-v01/validate_full_training.py @@ -0,0 +1,302 @@ +"""One bounded full-training cache validation; no fitting or native simulation. + +The unchanged strict exporter runs once per selected training recording, inside +each cache build. Previously sealed model dataset identities are the independent +golden references. No redundant strict export or held-out recording is read. +""" +import argparse +from datetime import datetime, timezone +from hashlib import sha256 +import gc +import json +import os +from pathlib import Path +import platform +import resource +import shutil +import sys +import time + +import numpy as np +from dvidia_training import camera_action_cache as cache +from dvidia_training import camera_action_export as export +from dvidia_training import camera_action_model as model + +parser = argparse.ArgumentParser(description=__doc__) +parser.add_argument('study', type=Path, help='Exact sealed v0.1 study (protocol and episode hashes remain pinned).') +parser.add_argument('output', type=Path, help='Fresh output directory outside the study; its parent must exist.') +parser.add_argument('--expected-venv', required=True, type=Path, help='Independently verified dev5 environment prefix.') +parser.add_argument('--working-directory', required=True, type=Path, help='Expected neutral directory outside the checkout.') +args = parser.parse_args() +if not all(path.is_absolute() for path in (args.study, args.output, args.expected_venv, args.working_directory)): + parser.error('All paths must be absolute; use the real virtual-environment and working-directory paths.') +STUDY = args.study +OUTPUT = args.output +PROOFS = OUTPUT.parent +VENV = args.expected_venv +WORKING_DIRECTORY = args.working_directory +SOURCE_COMMIT = 'cc6746a95669cfd69a49e32a3e6c2e5a42ce2546' +SOURCE_SHA = '0ab01145c66d651eaca96d763b4bec1706327f2cdd4bd8665d05056cbdd6f677' +CACHE_SHA = '9191f2eb9f96bd09d4f711c31966a583bd938853a874e6018f8ddebfb0bc00d8' +PROTOCOL_SHA = '576851e321034a0f6d3cb4d0818b3a5ca97975fcc6f2c7fa30b07ffd203a2d76' +STAGE_SHA = { + 'demonstrations': '5d57eac599f1686d2bdb15bb53ceebe09e899ec71dfe87039aa85de7f853c06b', + 'corrections': 'ae0a5653f728f147f929325c60318cb3d164c6d97d846fb96ac07ee9d27ad5cb', + 'train-initial': '86be5d9c17af43c35e97677d819b1433faed54ccf930078afc0f785139acc6a9', + 'train-corrected': '9b37a37d7b49fceb595f776d59579986f7579c7135f810b8d706199d5e4d6ddc', +} +GOLDEN = { + 'initial/full': { + 'model_sha256': '1d1f80376c89995513b518b36c4f8eca9e78efec3d3e68a10ee9988e84f4f038', + 'dataset_sha256': '07b175f78e4e77cbdde9a461a4bcae4dcb0db7d389ee4f2e702ff28db8bb3dfc', + 'provenance_sha256': '7103ad53111cb114cdcd164cfa15bbbf359ebc4ae66e7456ab7c1f38820b2864', + 'samples': 64000, + }, + 'initial/blind': { + 'model_sha256': 'd30b0ae10a4fbdc34a73122a34d73fd9246ee4b87c90c2b3b1eb3a98888d707e', + 'dataset_sha256': '759fe1c0610c1768f1455ed6cdcc6305be0d463b2b1e9c48a327f4f45b9c50c7', + 'provenance_sha256': '7d5279ffd186f018a41641a18bf5d6bbf010036114abb9e902d25aadc9ca3716', + 'samples': 64000, + }, + 'corrected/full': { + 'model_sha256': 'd176b391b61b5e331bcfe1676107c53f4c0ae6110414dfed4b07d57cbb883b0e', + 'dataset_sha256': 'b500b3ba348bba44cc79e377266f92910bd7e0165c36cd8b2fe260909b30a2f9', + 'provenance_sha256': '52cbeda62e3aa50e8cd6a34688fba7583f9fcec927cb0eb434a6907c99695f4f', + 'samples': 96000, + }, + 'corrected/blind': { + 'model_sha256': 'c3593d83b5505127a31304c8965914e01661d419dfc6c76a17a6c9bbac418806', + 'dataset_sha256': 'efd1760344b88c9eb61045454968564bb45a8cd38037e2bdcdf55b343eab3903', + 'provenance_sha256': '60edeb423d3810419e5ac971511c237c77e619a309637402b0974e658d7cb4a4', + 'samples': 96000, + }, +} +EXPECTED_RAW = { + 'demonstrations': {'episodes': 64, 'samples': 64000, 'files': 384704, 'bytes': 12638094084}, + 'corrections': {'episodes': 32, 'samples': 32000, 'files': 192352, 'bytes': 6333838508}, +} +RESERVE = 30 * 1024**3 +MAX_CACHE_BYTES = 128 * 1024**2 + + +def now(): + return datetime.now(timezone.utc).isoformat() + + +def identity(path): + body = path.read_bytes() + return {'bytes': len(body), 'sha256': sha256(body).hexdigest()} + + +def read_pinned(path, expected): + if path.is_symlink() or not path.is_file(): + raise ValueError('Expected a plain pinned metadata file.') + body = path.read_bytes() + if sha256(body).hexdigest() != expected: + raise ValueError('Independent input pin differs: ' + str(path)) + return json.loads(body) + + +def write_fresh(path, value): + with path.open('x') as stream: + json.dump(value, stream, indent=2, sort_keys=True, allow_nan=False) + stream.write('\n') + + +def save_status(state): + temporary = OUTPUT / 'status.pending.json' + temporary.write_text(json.dumps(state, indent=2, sort_keys=True) + '\n') + temporary.replace(OUTPUT / 'status.json') + + +def progress(state, stage, **fields): + row = {'at': now(), 'stage': stage, **fields} + with (OUTPUT / 'progress.jsonl').open('a') as stream: + stream.write(json.dumps(row, sort_keys=True, allow_nan=False) + '\n') + state.update(updated_at=row['at'], last_stage=stage, free_bytes=shutil.disk_usage(OUTPUT).free) + if state['free_bytes'] < RESERVE: + raise ValueError('Preserve the 30 GiB reserve.') + save_status(state) + print(json.dumps(row, sort_keys=True), flush=True) + + +def preflight(): + if Path(sys.prefix) != VENV or not Path(cache.__file__).is_relative_to(VENV): + raise ValueError('Use the existing independently verified dev5 installation.') + if 'PYTHONPATH' in os.environ or Path.cwd() != WORKING_DIRECTORY: + raise ValueError('Run from the supplied neutral directory outside the checkout, with PYTHONPATH unset.') + if cache.source_digest() != SOURCE_SHA or identity(Path(cache.__file__))['sha256'] != CACHE_SHA: + raise ValueError('Installed cache/runtime/feature source differs from reviewed cc6746a bytes.') + if model.FEATURE_COUNT != 269 or (STUDY / 'worker.lock').exists(): + raise ValueError('Unexpected feature contract or active study worker.') + protocol = read_pinned(STUDY / 'protocol.json', PROTOCOL_SHA) + stages = {} + for stage, digest in STAGE_SHA.items(): + stages[stage] = read_pinned(STUDY / 'stages' / (stage + '.json'), digest) + seal = json.loads((STUDY / 'stages' / (stage + '.integrity.json')).read_bytes()) + if seal != {'protocol_sha256': PROTOCOL_SHA, 'sha256': digest}: + raise ValueError('Sealed stage differs from independently pinned evidence.') + rosters, raw = {}, {} + for stage in EXPECTED_RAW: + # Protocol owns training membership and order; cache build revalidates + # every registration, stage, eligibility, source byte and sidecar binding. + rows = [row for row in stages[stage]['rows'] if row['case']['split'] == 'train'] + registered = [row for row in protocol['rosters'][stage] if row['case']['split'] == 'train'] + if [row['id'] for row in rows] != [row['id'] for row in registered]: + raise ValueError('Ordered training roster differs.') + total_files = total_bytes = 0 + for row in rows: + if (row.get('complete') is not True or row.get('initial_anchor_available') is not True + or row.get('initial_anchor_binding_valid') is not True + or row['recorded_complete_intervals'] != 1000 + or (stage == 'demonstrations' and row.get('strict_success') is not True)): + raise ValueError('Do not replace or drop an ineligible training episode.') + expected_path = f'episodes/{stage}/{row["id"]}' + if row['path'] != expected_path: + raise ValueError('Training path differs from sealed registered identity.') + path = STUDY / expected_path / 'integrity.json' + inventory = read_pinned(path, row['integrity_sha256']) + total_files += len(inventory['files']) + 1 + total_bytes += sum(item['bytes'] for item in inventory['files'].values()) + path.stat().st_size + raw[stage] = {'episodes': len(rows), 'samples': sum(row['recorded_complete_intervals'] for row in rows), + 'files': total_files, 'bytes': total_bytes} + if raw[stage] != EXPECTED_RAW[stage]: + raise ValueError('Raw training inventory differs from the prepared bounds.') + rosters[stage] = [row['id'] for row in rows] + training = {} + for name, expected in GOLDEN.items(): + stage, variant = name.split('/') + document = read_pinned(STUDY / 'models' / name / 'model.json', expected['model_sha256']) + reference = stages['train-' + stage]['models'][variant] + record = document['training'] + expected_episodes = rosters['demonstrations'] + (rosters['corrections'] if stage == 'corrected' else []) + if (reference['model_sha256'] != expected['model_sha256'] or reference['training'] != record + or reference['training_episodes'] != expected_episodes + or record['sample_count'] != expected['samples'] + or record['dataset_sha256'] != expected['dataset_sha256'] + or record['provenance_sha256'] != expected['provenance_sha256'] + or model.digest(record['provenance']) != expected['provenance_sha256']): + raise ValueError('Model dataset reference differs from sealed fit-stage evidence.') + training[name] = record + return rosters, raw, training + + +def match_golden(dataset, name, training): + _, _, groups, provenance, digest = model._dataset(dataset, blind=name.endswith('/blind')) + expected = GOLDEN[name] + if (digest != expected['dataset_sha256'] or len(groups) != expected['samples'] + or provenance != training[name]['provenance'] + or model.digest(provenance) != expected['provenance_sha256'] + or list(dict.fromkeys(groups)) != training[name]['train_groups']): + raise ValueError('Loaded complete dataset does not equal its independently sealed model reference: ' + name) + return {'name': name, 'passed': True, 'dataset_sha256': digest, + 'model_sha256': expected['model_sha256'], 'samples': len(groups), + 'groups': len(set(groups)), 'episodes': len(provenance['episodes']), + 'provenance_sha256': model.digest(provenance)} + + +def main(): + if OUTPUT.exists() or OUTPUT.is_symlink() or STUDY in OUTPUT.parents: + raise ValueError('Fresh output outside study required; retain any interrupted prefix.') + if shutil.disk_usage(PROOFS).free < RESERVE + 256 * 1024**2: + raise ValueError('Require 30 GiB reserve plus bounded cache/log headroom.') + OUTPUT.mkdir(mode=0o700) + lock = OUTPUT / 'worker.lock' + write_fresh(lock, {'pid': os.getpid(), 'started_at': now(), 'workers': 1}) + state = {'schema': 'dvidia.full-training-cache-process/v1', 'state': 'running', + 'pid': os.getpid(), 'started_at': now(), 'native_runs': 0, 'fitting_runs': 0} + save_status(state) + started = time.perf_counter() + try: + rosters, raw, training = preflight() + retained = {'source_commit': SOURCE_COMMIT, 'source_sha256': SOURCE_SHA, + 'cache_source_sha256': CACHE_SHA, 'source_identity': cache.source_identity(), + 'protocol_sha256': PROTOCOL_SHA, 'stage_sha256': STAGE_SHA, + 'model_references': GOLDEN, 'attempt_ids': rosters, 'raw_training_inventory': raw, + 'validation_script': identity(Path(__file__))} + write_fresh(OUTPUT / 'independent-input-pins.json', retained) + (OUTPUT / 'independent-input-pins.json').chmod(0o444) + progress(state, 'preflight', episodes=96, samples=96000, raw_inventory=raw) + pins, builds = {}, [] + for stage in ('demonstrations', 'corrections'): + began = time.perf_counter() + pin = cache.build_cache(STUDY, OUTPUT / (stage + '-cache'), + expected_protocol_sha256=PROTOCOL_SHA, split='train', stage=stage, + attempt_ids=rosters[stage], blind=False) + elapsed = time.perf_counter() - began + if pin['sample_count'] != EXPECTED_RAW[stage]['samples'] or pin['source_sha256'] != SOURCE_SHA: + raise ValueError('Build pin differs from registered scope.') + write_fresh(OUTPUT / (stage + '-pins.json'), pin) + (OUTPUT / (stage + '-pins.json')).chmod(0o444) + pins[stage] = pin + sizes = sum(path.stat().st_size for path in (OUTPUT / (stage + '-cache')).iterdir()) + builds.append({'stage': stage, 'seconds': elapsed, 'cache_bytes': sizes, 'pins': pin}) + progress(state, 'cache_built', cache_stage=stage, seconds=elapsed, cache_bytes=sizes, pins=pin) + gc.collect() + if sum(row['cache_bytes'] for row in builds) > MAX_CACHE_BYTES: + raise ValueError('Derived caches exceed the declared 128 MiB bound.') + rounds = [] + for index in range(3): + round_start = time.perf_counter() + datasets, loads = {}, {} + for stage in ('demonstrations', 'corrections'): + pin = pins[stage] # retained independently, never self-read from cache + began = time.perf_counter() + datasets[stage] = cache.load_cache(OUTPUT / (stage + '-cache'), + expected_manifest_sha256=pin['manifest_sha256'], expected_protocol_sha256=PROTOCOL_SHA, + expected_split='train', expected_source_sha256=SOURCE_SHA) + loads[stage] = time.perf_counter() - began + began = time.perf_counter() + combined = export.combine_datasets([datasets['demonstrations'], datasets['corrections']]) + combine_seconds = time.perf_counter() - began + began = time.perf_counter() + checks = [match_golden(datasets['demonstrations'], 'initial/full', training), + match_golden(combined, 'corrected/full', training)] + for dataset, name in ((datasets['demonstrations'], 'initial/blind'), (combined, 'corrected/blind')): + blinded = export.blind_dataset(dataset) + checks.append(match_golden(blinded, name, training)) + del blinded + comparison_seconds = time.perf_counter() - began + rounds.append({'round': index + 1, 'validated_load_seconds': loads, + 'combine_seconds': combine_seconds, + 'golden_comparison_and_blind_projection_seconds': comparison_seconds, + 'whole_round_seconds': time.perf_counter() - round_start, 'checks': checks}) + progress(state, 'validated_round', **rounds[-1]) + del dataset, datasets, combined + gc.collect() + # Recheck small source/stage/model/episode manifest pins without a second + # raw export. A cache hit never asserts that raw frames were revalidated. + if preflight() != (rosters, raw, training): + raise ValueError('Independent metadata changed during measurement.') + peak = resource.getrusage(resource.RUSAGE_SELF).ru_maxrss + result = {'schema': 'dvidia.full-training-cache-validation/v1', 'passed': True, + **retained, 'builds': builds, 'rounds': rounds, + 'raw_training_files': sum(row['files'] for row in raw.values()), + 'raw_training_bytes': sum(row['bytes'] for row in raw.values()), + 'derived_cache_bytes': sum(row['cache_bytes'] for row in builds), + 'peak_process_rss_bytes': int(peak) * (1 if sys.platform == 'darwin' else 1024), + 'hardware': {'platform': platform.platform(), 'machine': platform.machine(), + 'python': platform.python_version(), 'numpy': np.__version__}, + 'wall_seconds': time.perf_counter() - started, 'raw_source_reverified_on_hit': False, + 'native_runs': 0, 'fitting_runs': 0, 'extra_strict_exports': 0, + 'development_or_confirmation_recordings_read': False, 'qualification_changed': False, + 'comparison_scope': 'Canonical float64 numeric values, ordered groups and full provenance equal the four independently sealed model dataset identities; cache float32 storage is not original combined NPY byte identity.', + 'timing_scope': 'Shared-host offline preparation. Imports excluded; builds include strict source, sidecar and saved-trace score validation. Each hit includes cache/source validation. Combiner and golden checks reported separately. No cold-cache flush, isolated CPU reservation or matched strict-export timing; no speedup claim.', + 'memory_scope': 'Whole-process high-water RSS across metadata inspection, both builds, loads, combination and golden checks; not isolated per-stage memory.', + 'source_read_scope': 'Unique raw corpus size is metadata-bound, not measured physical I/O. Strict exporter rereads some metadata, sidecars and native trace bytes; no physics is executed.'} + write_fresh(OUTPUT / 'result.json', result) + state.update(state='completed', completed_at=now(), elapsed_seconds=time.perf_counter()-started, + result=identity(OUTPUT / 'result.json'), exit_code=0) + save_status(state) + lock.unlink() + print(json.dumps({'passed': True, 'result': str(OUTPUT / 'result.json'), + 'result_identity': identity(OUTPUT / 'result.json')}, sort_keys=True), flush=True) + except BaseException as exc: + state.update(state='interrupted_or_failed', updated_at=now(), exception_type=type(exc).__name__, + reason=str(exc), elapsed_seconds=time.perf_counter()-started) + save_status(state) + raise # retain all prefixes, independent pins and worker lock + + +if __name__ == '__main__': + main() diff --git a/docs/camera-action-export-cache-v01.md b/docs/camera-action-export-cache-v01.md index d63577e..ee95796 100644 --- a/docs/camera-action-export-cache-v01.md +++ b/docs/camera-action-export-cache-v01.md @@ -77,6 +77,37 @@ A fresh offline `0.1.3.dev5` wheel install outside the checkout matched the curr This measures repeated data preparation only. It is not evidence of faster policy inference, better grip/placement success, whole-study throughput or physical-arm readiness. The v0.1 learned result remains 5/64 strict unseen placements and unqualified. +## Complete training-data validation + +A separate, single construction pass validated **all 64 teacher demonstrations and 32 mixed-control correction recordings** from the registered training split: 96,000 action samples across 32 starting-position groups. The cache used the unchanged `cc6746a95669cfd69a49e32a3e6c2e5a42ce2546` implementation. No development or confirmation recordings were exported and no model was fitted. + +The four original model files provide independent, pinned dataset references. On each of three loads, the initial/full, initial/blind, corrected/full and corrected/blind dataset hashes, ordered groups and complete provenance matched those sealed references: **12/12 checks passed**. The blind variants use the unchanged exporter mask; corrections retain separately queried teacher labels. This validates the complete existing training dataset, beyond the earlier one-episode check. + +| Operation | Wall time | +|---|---:| +| Build 64-demonstration cache, including strict source validation | 105.621 s | +| Build 32-correction cache, including strict source validation | 55.050 s | +| One-time construction total | 160.671 s | +| Validated load of both caches plus ordered combination, rounds 1 / 2 / 3 | 0.347 / 0.280 / 0.279 s | +| Separate four-reference checks and blind projection, rounds 1 / 2 / 3 | 0.596 / 0.491 / 0.490 s | + +The derived caches occupy **108,804,852 bytes**. Their source inventory contains 577,056 files and 18,971,932,592 bytes; this is the unique corpus size, not a physical-I/O measurement. Whole-process peak RSS was 1,631,633,408 bytes across construction, loads, combination and reference checks. Total validation took 163.738 s. The original raw recordings remain intact, with the 30 GiB reserve preserved. + +These are shared-host, warm-filesystem preparation measurements on the same arm64 macOS / Python 3.12.9 / NumPy 2.5.3 environment; CPU model and physical-memory metadata were unavailable. No matched strict-export baseline was rerun, so **there is no whole-pipeline speedup ratio**. The roughly 0.28 s repeated load-and-combine measurement excludes model fitting and the separately reported golden checks. It does not change inference speed, task success or qualification: the learned candidate remains **unqualified** (`qualified: false`). Cache hits still do not revalidate raw recordings. + +The [full-training receipt](../benchmarks/camera-action-export-cache-v01/full-training-results.json) records every timing, cache pin and original model identity. The [portable helper](../benchmarks/camera-action-export-cache-v01/validate_full_training.py) changes only host paths into required CLI inputs; its [provenance record](../benchmarks/camera-action-export-cache-v01/full-training-script-provenance.json) distinguishes its hash from the exact original script that produced these measurements. The portable helper was not used for another measurement. It requires the exact pinned study and the independently verified dev5 environment; it refuses changed sources, wrong models, missing training recordings and an existing output directory. + +```sh +cd /absolute/neutral-work-directory +env -u PYTHONPATH /absolute/dev5/bin/python -I -B \ + /absolute/dvidia-training/benchmarks/camera-action-export-cache-v01/validate_full_training.py \ + /absolute/sealed-study /absolute/fresh-output \ + --expected-venv /absolute/dev5 \ + --working-directory /absolute/neutral-work-directory +``` + +Keep the study sealed and give the process exclusive write access to its fresh output. This helper performs two strict cache builds and three validation rounds; it does not start training, execute a policy, run physics or download anything. Interrupted output is retained and never silently overwritten. The released dev5 wheel and tag remain unchanged by this benchmark-only addition. + ## Reproduce the bounded measurement ```sh